61 resultados para Market data approach


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In the literature on housing market areas, different approaches can be found to defining them, for example, using travel-to-work areas and, more recently, making use of migration data. Here we propose a simple exercise to shed light on which approach performs better. Using regional data from Catalonia, Spain, we have computed housing market areas with both commuting data and migration data. In order to decide which procedure shows superior performance, we have looked at uniformity of prices within areas. The main finding is that commuting algorithms present more homogeneous areas in terms of housing prices.

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The purpose of this paper is to study the determinants of equilibrium in the market for daily funds. We use the EONIA panel database which includes daily information on the lending rates applied by contributing commercial banks. The data clearly shows an increase in both the time series volatility and the cross section dispersion of rates towards the end of the reserve maintenance period. These increases are highly correlated. With respect to quantities, we find that the volume of trade as well as the use of the standing facilities are also larger at the end of the maintenance period. Our theoretical model shows how the operational framework of monetary policy causes a reduction in the elasticity of the supply of funds by banks throughout the reserve maintenance period. This reduction in the elasticity together with market segmentation and heterogeneity are able to generate distributions for the interest rates and quantities traded with the same properties as in the data.

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We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that, after correcting for measurement error bias, the value of this parameter is well above 0.50.

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We study whether people's behavior in unbalanced gift exchange markets with repeated interaction are affected by whether they are on the excess supply side or the excess demand side of the market. Our analysis is based on the comparison of behavior between two types of experimental gift exchange markets, which vary only with respect to whether first or second movers are on the long side of the market. The direction of market imbalance could influence subjects' behavior, as second movers (workers) might react differently to favorable actions by first movers (firms) in the two cases. While our data show strong deviations from the standard game-theoretic prediction, we find mainly secondary treatment effects. Wage offers are not higher when there is an excess supply of firms, and workers do not respond more favorably to a given wage when there is an excess supply of labor. The state of competition does not appear to have strong effects in our data. We also present data from single-period sessions that show substantial gift exchange even without repeated interactions.

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We study markets where the characteristics or decisions of certain agents are relevant but not known to their trading partners. Assuming exclusive transactions, the environment is described as a continuum economy with indivisible commodities. We characterize incentive efficient allocations as solutions to linear programming problems and appeal to duality theory to demonstrate the generic existence of external effects in these markets. Because under certain conditions such effects may generate non-convexities, randomization emerges as a theoretic possibility. In characterizing market equilibria we show that, consistently with the personalized nature of transactions, prices are generally non-linear in the underlying consumption. On the other hand, external effects may have critical implications for market efficiency. With adverse selection, in fact, cross-subsidization across agents with different private information may be necessary for optimality, and so, the market need not even achieve an incentive efficient allocation. In contrast, for the case of a single commodity, we find that when informational asymmetries arise after the trading period (e.g. moral hazard; ex post hidden types) external effects are fully internalized at a market equilibrium.

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The last 20 years have seen a significant evolution in the literature on horizontal inequity (HI) and have generated two major and "rival" methodological strands, namely, classical HI and reranking. We propose in this paper a class of ethically flexible tools that integrate these two strands. This is achieved using a measure of inequality that merges the well-known Gini coefficient and Atkinson indices, and that allows a decomposition of the total redistributive effect of taxes and transfers in a vertical equity effect and a loss of redistribution due to either classical HI or reranking. An inequality-change approach and a money-metric cost-of-inequality approach are developed. The latter approach makes aggregate classical HI decomposable across groups. As in recent work, equals are identified through a nonparametric estimation of the joint density of gross and net incomes. An illustration using Canadian data from 1981 to 1994 shows a substantial, and increasing, robust erosion of redistribution attributable both to classical HI and to reranking, but does not reveal which of reranking or classical HI is more important since this requires a judgement that is fundamentally normative in nature.

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In this paper we check whether generator's bid behavior at the Spanish whosale electricity market is consistent with the hypothesis of profit maximization on their residual demands. Using OMEL data, we find the arc-elacticity of the residual demand around the system marginal price. The results suggest thet the larger firms are not actually profit-msximization. We argue how the regulatory environment may drive these results. Finally, we repeat the analysis for the first session of the intra-day market where presumably firms may not have the same incentives as in the day-ahead market.

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Export activities are a major source of economic growth and are considered important both at the national level and for individual businesses. Moreover, in the case of SMEs, they gain particular relevance, exporting being the most common foreign market entry mode for these firms. The decision maker’s role in the export activity is crucial, particularly in the case of SMEs. However, the extant literature on internationalization is characterized by a lack of consensus among scholars as to what constitutes the managerial factor in determining exporting. Therefore, this study focuses on the following issue: Which are the decision maker’s characteristics and perceptions that may influence the export behaviour of Catalan SMEs? To address this question a multiple case study method is applied across four Catalan exporting SMEs. The methodology chosen for analysing the empirical data is relying on the proposition testing approach while the investigation is conducted including both within and cross-case analysis. The findings show that high educational level, language skills, high risk tolerance, innovativeness as well as strongly perceived export stimuli as compared to low and easy to overcome export barriers positively influence the export involvement and development of SMEs. The study provides further insights into the research topic by jointly studying managerial characteristics and perceptions. Additionally, the majority of research on exporting topics has been carried out in the USA, so there is a clear need of investigation in the field in other countries, moreover in Spain where the exporting activities have not been as widely studied.

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The relationships between economic growth and environmental pressures are complex. Since the early nineties, the debate on these relationships has been strongly influenced by the Environmental Kuznets Curve hypothesis, which states that during the first stage of economic development environmental pressures increase as per capita income increases, but once a critical turning-point has been reached these pressures diminish as income levels continue to increase. However, to date such a delinking between economic growth and emission levels has not happened for most atmospheric pollutants in Spain. The aim of this paper is to analyse the relationship between income growth and nine atmospheric pollutants in Spain. In order to obtain empirical outcomes for this analysis, we adopt an input-output approach and use NAMEA data for the nine pollutants. First, we undertake a structural decomposition analysis for the period 1995-2000 to estimate the contribution of various factors to changes in the levels of atmospheric emissions. And second, we estimate the emissions associated with the consumption patterns of different groups of households classified according to their level of expenditure

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The aim of this article is to assess the effects of several territorial characteristics, specifically agglomeration economies, on industrial location processes in the Spanish region of Catalonia. Theoretically, the level of agglomeration causes economies which favour the location of new establishments, but an excessive level of agglomeration might cause diseconomies, since congestion effects arise. The empirical evidence on this matter is inconclusive, probably because the models used so far are not suitable enough. We use a more flexible semiparametric specification, which allows us to study the nonlinear relationship between the different types of agglomeration levels and location processes. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new industrial establishments. Keywords: agglomeration economies, industrial location, Generalized Additive Models, nonparametric estimation, count data models.

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Using a newly constructed data set, we calculate quality-adjusted price indexes after estimating hedonic price regressions from 1988 to 2004 in the Spanish automobile market. The increasing competition was favoured by the removal of trade restrictions and the special plans for the renewal of the Spanish automobile fleet. We find that the increasing degree of competition during those years led to an overall drop in automobile prices by 20 percent which implied considerable consumer gains thanks to higher market efficiency. Additionally, our results indicate that loyalty relevance and discrepancies in automobile reliability declined during those years. This is captured.

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There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.

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Within last few years a new type of instruments called Terrestrial Laser Scanners (TLS) entered to the commercial market. These devices brought a possibility to obtain completely new type of spatial, three dimensional data describing the object of interest. TLS instruments are generating a type of data that needs a special treatment. Appearance of this technique made possible to monitor deformations of very large objects, like investigated here landslides, with new quality level. This change is visible especially with relation to the size and number of the details that can be observed with this new method. Taking into account this context presented here work is oriented on recognition and characterization of raw data received from the TLS instruments as well as processing phases, tools and techniques to do them. Main objective are definition and recognition of the problems related with usage of the TLS data, characterization of the quality single point generated by TLS, description and investigation of the TLS processing approach for landslides deformation measurements allowing to obtain 3D deformation characteristic and finally validation of the obtained results. The above objectives are based on the bibliography studies and research work followed by several experiments that will prove the conclusions.

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This paper compares the poverty reduction impact of income sources, taxes and transfers across five OECD countries. Since the estimation of that impact can depend on the order in which the various income sources are introduced into the analysis, it is done by using the Shapley value. Estimates of the poverty reduction impact are presented in a normalized and un-normalized fashion, in order to take into into account the total as well as the per dollar impacts. The methodology is applied to data from the Luxembourg Income Study (LIS) database.

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This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.