Calculation of the variance in surveys of the economic climate

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated. As in any survey conducted on a sample the question of the measurement of the sample error of the results has to be addressed, since the error influences both the reliability of the results and the calculation of the sample size adequate for a desired confidence interval. The results presented here are based on data from the Survey of the Business Climate (Encuesta de Clima Empresarial) developed through the collaboration of the Statistical Institute of Catalonia (Institut d’Estadística de Catalunya) with the Chambers of Commerce (Cámaras de Comercio) of Sabadell and Terrassa.

How reliable is the monitoring of permanent vegetation plots? A test with multiple observers

Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Market Familiarity and the Location of South and North MNEs

We use a systematic empirical analysis of the determinants of South-South (SS) and North-South (NS) foreign direct investment (FDI) as a canvas to explore how multinational enterprises’ (MNEs) location decisions are shaped by better acquaintance with a foreign market resulting from bilateral ties, experience of international expansion, and knowledge of how to deal with poor governance. We find that these various aspects of market familiarity, which can interact together, are important to explain and differentiate the location behaviours of South MNEs (S-MNEs) and North MNEs (N-MNEs) in developing countries.

Employment Protection, Flexibility and Firms’ Strategic Location Decisions under Uncertainty

We construct a model in which oligopolistic firms decide between locating in a country where employment protection implies costly output adjustments and in one without employment protection. Using a two-period three-stage game with uncertainty, we demonstrate that location is influenced by both flexibility and strategic concerns. The strategic effects under Cournot work towards domestic anchorage in the country with employment protection while those under Bertrand do not. Strategic agglomeration can occur in the inflexible country under Cournot and even under Bertrand, provided uncertainty and foreign direct investment costs are low.

(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

A critical analysis of dimensions and curve fitting practice in economics

When dealing with sustainability we are concerned with the biophysical as well as the monetary aspects of economic and ecological interactions. This multidimensional approach requires that special attention is given to dimensional issues in relation to curve fitting practice in economics. Unfortunately, many empirical and theoretical studies in economics, as well as in ecological economics, apply dimensional numbers in exponential or logarithmic functions. We show that it is an analytical error to put a dimensional unit x into exponential functions ( a x ) and logarithmic functions ( x a log ). Secondly, we investigate the conditions of data sets under which a particular logarithmic specification is superior to the usual regression specification. This analysis shows that logarithmic specification superiority in terms of least square norm is heavily dependent on the available data set. The last section deals with economists’ “curve fitting fetishism”. We propose that a distinction be made between curve fitting over past observations and the development of a theoretical or empirical law capable of maintaining its fitting power for any future observations. Finally we conclude this paper with several epistemological issues in relation to dimensions and curve fitting practice in economics

Spatial and temporal distribution of anopheline larvae in two malarious areas in Sucre State, Venezuela

The spatial and temporal distribution of anopheline larvae was studied in two coastal malarious areas of Sucre, State, Venezuela. Seven habitat types were sampled in the village of Guayana and eight species of Anopheles were collected. Anopheles aquasalis was the predominant species collected and was most abundant in the brackish marsh habitat (71 larvae per 100 samples). It was most abundant during the rainy season. At the second location, Santa F e, six habitat types were sampled and four anopheline species were collected. Habitats where An. aquasalis was most abundant were temporary freshwater ponds (34 larvae per 100 samples) and mangroves (10.5 larvae per 100 samples). At this location it was also most abundant in the rainy season. During the dry season it was collected in small numbers in river pools (1.3 larvae per 100 samples) along with large numbers of An. pseudopunctipennis (479 larvae per 100 samples). Larval control could be an important component of the malaria control program because major habitats could be defined and presence and abundance of larvae was limited to specific times of year.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Dukes B colorectal cancer: distinct genetic categories and clinical outcome based on proximal or distal tumor location.

PURPOSE: The aim of this study was to determine whether tumor location proximal or distal to the splenic flexure is associated with distinct molecular patterns and can predict clinical outcome in a homogeneous group of patients with Dukes B (T3-T4, N0, M0) colorectal cancer. It has been hypothesized that proximal and distal colorectal cancer may arise through different pathogenetic mechanisms. Although p53 and Ki-ras gene mutations occur frequently in distal tumors, another form of genomic instability associated with defective DNA mismatch repair has been predominantly identified in the proximal colon. To date, however, the clinical usefulness of these molecular characteristics remains unproven. METHODS: A total of 126 patients with a lymph node-negative sporadic colon or rectum adenocarcinoma were prospectively assessed with the endpoint of death by cancer. No patient received either radiotherapy or chemotherapy. p53 protein was studied by immunohistochemistry using DO-7 monoclonal antibody, and p53 and Ki-ras gene mutations were detected by single strand conformation polymorphism assay. RESULTS: During a mean follow-up of 67 months, the overall five-year survival was 70 percent. Nuclear p53 staining was found in 57 tumors (47 percent), and was more frequent in distal than in proximal tumors (55 vs. 21 percent; chi-squared test, P < 0.001). For the whole group, p53 protein expression correlated with poor survival in univariate and multivariate analysis (log-rank test, P = 0.01; hazard ratio = 2.16; 95 percent confidence interval = 1.12-4.11, P = 0.02). Distal colon tumors and rectal tumors exhibited similar molecular patterns and showed no difference in clinical outcome. In comparison with distal colorectal cancer, proximal tumors were found to be statistically significantly different on the following factors: mucinous content (P = 0.008), degree of histologic differentiation (P = 0.012), p53 protein expression, and gene mutation (P = 0.001 and 0.01 respectively). Finally, patients with proximal tumors had a marginally better survival than those with distal colon or rectal cancers (log-rank test, P = 0.045). CONCLUSION: In this series of Dukes B colorectal cancers, p53 protein expression was an independent factor for survival, which also correlated with tumor location. Eighty-six percent of p53-positive tumors were located in the distal colon and rectum. Distal colon and rectum tumors had similar molecular and clinical characteristics. In contrast, proximal neoplasms seem to represent a distinct entity, with specific histopathologic characteristics, molecular patterns, and clinical outcome. Location of the neoplasm in reference to the splenic flexure should be considered before group stratification in future trials of adjuvant chemotherapy in patients with Dukes B tumors.

Mechanisms of agglomeration: Evidence from the location of new manufacturing firms in Spain

El objetivo de esta investigación es aportar evidencia sobre las fuentes de las economías de aglomeración para el caso español. De todas las maneras posibles que se han tomado en la literatura para medir las economías de aglomeración, nosotros lo analizamos a partir de las decisiones de localización de las empresas manufactureras. La literatura reciente ha puesto de relieve que el análisis basado en la disyuntiva localización / urbanización (relaciones dentro de un mismo sector) no es suficiente para entender las economías de aglomeración. Sin embargo, las relaciones entre los diferentes sectores sí resultan significativas al examinar por qué las empresas que pertenecen a diferentes sectores se localizan unas al lado de las otras. Con esto en mente, intentamos explicar que relaciones entre diferentes sectores pueden explicar coaglomeración. Para ello, nos centramos en aquellas relaciones entre sectores definidos a partir de los mecanismos de aglomeración de Marshall, es decir, labor market, input sharing y knowledge spillovers. Trabajamos con el labor market pooling en la medida en que los dos sectores utilizan los mismos trabajadores (clasificación de ocupaciones). Con el segundo mecanismo de Marshall, input sharing, introducimos cómo dos sectores tienen una relación de comprador / vendedor. Por último, nos referimos a dos sectores que utilizan las mismas tecnologías en cuanto a los knowledge spillovers. Con el fin de capturar todos los efectos de los mecanismos de aglomeracion en España, en esta investigación trabajamos con dos ámbitos geográficos, los municipios y los mercados de trabajo locales. La literatura existente nunca se ha puesto de acuerdo en cual es el ámbito geográfico en el que mejor trabajan los mecanismos Marshall, por lo que hemos cubierto todas las unidades geográficas potenciales.

Chromosome numbers in the Triatominae (Hemiptera-Reduviidae): a review

The chromosome numbers of 46 out of the 122 currently recognized species of Triatominae (Hemiptera, Reduviidae) are summarized. We present the number of autosomes, the sex mechanism and the first reference for each karyotype.

On the effect of the geographical scope of agglomeration economies on firm location

This article analyses how agglomeration economies shaped the location decisions of new manufacturing start-ups in Catalan municipalities in 2001-2005. We estimate whether the locations of new firms are spatially autocorrelated and whether this phenomenon is industry-specific. Our aim is to estimate the geographical scope of agglomeration economies on firm entries. The data set comes from a compulsory register of manufacturing establishments (REIC: Catalan Manufacturing Establishments Register). JEL classification: R1, R3 Keywords: firm location; spatial autocorrelation

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.