29 resultados para structural equation analysis


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Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

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Analysis of gas emissions by the input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO2 emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 1990 and 2000. Our results show that services increased their CO2 emissions mainly because of a rise in emissions generated by non-services to cover the final demand for services. In all service activities, the decomposed effects show an increase in CO2 emissions due to a decrease in emission coefficients (i.e., emissions per unit of output) compensated by an increase in emissions caused both by the input-output coefficients and the rise in demand for services. Finally, large asymmetries exist not only in the quantitative changes in the CO2 emissions of the various services but also in the decomposed effects of these changes. Keywords: structural decomposition analysis, input-output subsystems, CO2 emissions, service sector.

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This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

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Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services

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Some past studies analyzed Spanish monetary policy with the standard VAR. Their problem is that this method obliges researchers to impose a certain extreme form of the short run policy rule on their models. Hence, it does not allow researchers to study the possibility of structural changes in this rule, either. This paper overcomes these problems by using the structural VAR. I find that the rule has always been that of partial accommodation. Prior to 1984, it was quite close to money targeting. After 1984, it became closer to the interest rate targeting, with more emphasis on the exchange rate.

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We develop and estimate a structural model of inflation that allowsfor a fraction of firms that use a backward looking rule to setprices. The model nests the purely forward looking New KeynesianPhillips curve as a particular case. We use measures of marginalcosts as the relevant determinant of inflation, as the theorysuggests, instead of an ad-hoc output gap. Real marginal costsare a significant and quantitatively important determinant ofinflation. Backward looking price setting, while statisticallysignificant, is not quantitatively important. Thus, we concludethat the New Keynesian Phillips curve provides a good firstapproximation to the dynamics of inflation.

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The complexity of the connexions within an economic system can only be reliably reflected in academic research if powerful methods are used. Researchers have used Structural Path Analysis (SPA) to capture not only the linkages within the production system but also the propagation of the effects into different channels of impacts. However, the SPA literature has restricted itself to showing the relations among sectors of production, while the connections between these sectors and final consumption have attracted little attention. In order to consider the complete set of channels involved, in this paper we propose a structural path method that endogenously incorporates not only sectors of production but also the final consumption of the economy. The empirical application comprises water usages, and analyses the dissemination of exogenous impacts into various channels of water consumption. The results show that the responsibility for water stress is imputed to different sectors and depends on the hypothesis used for the role played by final consumption in the model. This highlights the importance of consumers’ decisions in the determination of ecological impacts. Keywords: Input-Output Analysis, Structural Path Analysis, Final Consumption, Water uses.

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[spa] El estudio analiza la evolución de los gases de efecto invernadero (GEI) y las emisiones de acidificación para Italia durante el periodo 1995-2005. Los datos muestran que mientras las emisiones que contribuyen a la acidificación han disminuido constantemente, las emisiones de GEI han aumentado debido al aumento de dióxido de carbono. El objetivo de este estudio es poner de relieve cómo diferentes factores económicos, en particular el crecimiento económico, el desarrollo de una tecnología menos contaminante y la estructura del consumo, han impulsado la evolución de las emisiones. La metodología propuesta es un análisis de descomposición estructural (ADE), método que permite descomponer los cambios de la variable de interés entre las diferentes fuerzas y revelar la importancia de cada factor. Por otra parte, este estudio considera la importancia del comercio internacional e intenta incluir el “problema de la responsabilidad”. Es decir, a través de las relaciones comerciales internacionales, un país podría estar exportando procesos de producción contaminantes sin una reducción real de la contaminación implícita en su patrón de consumo. Con este fin, siguiendo primero un enfoque basado en la “responsabilidad del productor”, el ADE se aplica a las emisiones causadas por la producción nacional. Sucesivamente, el análisis se mueve hacia un enfoque basado en la “responsabilidad del consumidor" y la descomposición se aplica a las emisiones relacionadas con la producción nacional o la producción extranjera que satisface la demanda interna. De esta manera, el ejercicio permite una primera comprobación de la importancia del comercio internacional y pone de relieve algunos resultados a nivel global y a nivel sectorial.

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[spa] El estudio analiza la evolución de los gases de efecto invernadero (GEI) y las emisiones de acidificación para Italia durante el periodo 1995-2005. Los datos muestran que mientras las emisiones que contribuyen a la acidificación han disminuido constantemente, las emisiones de GEI han aumentado debido al aumento de dióxido de carbono. El objetivo de este estudio es poner de relieve cómo diferentes factores económicos, en particular el crecimiento económico, el desarrollo de una tecnología menos contaminante y la estructura del consumo, han impulsado la evolución de las emisiones. La metodología propuesta es un análisis de descomposición estructural (ADE), método que permite descomponer los cambios de la variable de interés entre las diferentes fuerzas y revelar la importancia de cada factor. Por otra parte, este estudio considera la importancia del comercio internacional e intenta incluir el “problema de la responsabilidad”. Es decir, a través de las relaciones comerciales internacionales, un país podría estar exportando procesos de producción contaminantes sin una reducción real de la contaminación implícita en su patrón de consumo. Con este fin, siguiendo primero un enfoque basado en la “responsabilidad del productor”, el ADE se aplica a las emisiones causadas por la producción nacional. Sucesivamente, el análisis se mueve hacia un enfoque basado en la “responsabilidad del consumidor" y la descomposición se aplica a las emisiones relacionadas con la producción nacional o la producción extranjera que satisface la demanda interna. De esta manera, el ejercicio permite una primera comprobación de la importancia del comercio internacional y pone de relieve algunos resultados a nivel global y a nivel sectorial.

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In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct

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Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

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The aim of this study is to confirm the factorial structure of the Identification-Commitment Inventory (ICI) developed within the frame of the Human System Audit (HSA) (Quijano et al. in Revist Psicol Soc Apl 10(2):27-61, 2000; Pap Psicól Revist Col Of Psicó 29:92-106, 2008). Commitment and identification are understood by the HSA at an individual level as part of the quality of human processes and resources in an organization; and therefore as antecedents of important organizational outcomes, such as personnel turnover intentions, organizational citizenship behavior, etc. (Meyer et al. in J Org Behav 27:665-683, 2006). The theoretical integrative model which underlies ICI Quijano et al. (2000) was tested in a sample (N = 625) of workers in a Spanish public hospital. Confirmatory factor analysis through structural equation modeling was performed. Elliptical least square solution was chosen as estimator procedure on account of non-normal distribution of the variables. The results confirm the goodness of fit of an integrative model, which underlies the relation between Commitment and Identification, although each one is operatively different.

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Mediterranean endemic freshwater fish are among the most threatened biota in the world. Distinguishing the role of different extinction drivers and their potential interactions is crucial for achieving conservation goals. While some authors argue that invasive species are a main driver of native species declines, others see their proliferation as a co-occurring process to biodiversity loss driven by habitat degradation. It is difficult to discern between the two potential causes given that few invaded ecosystems are free from habitat degradation, and that both factors may interact in different ways. Here we analyze the relative importance of habitat degradation and invasive species in the decline of native fish assemblages in the Guadiana River basin (southwestern Iberian Peninsula) using an information theoretic approach to evaluate interaction pathways between invasive species and habitat degradation (structural equation modeling, SEM). We also tested the possible changes in the functional relationships between invasive and native species, measured as the per capita effect of invasive species, using ANCOVA. We found that the abundance of invasive species was the best single predictor of natives’ decline and had the highest Akaike weight among the set of predictor variables examined. Habitat degradation neither played an active role nor influenced the per capita effect of invasive species on natives. Our analyses indicated that downstream reaches and areas close to reservoirs had the most invaded fish assemblages, independently of their habitat degradation status. The proliferation of invasive species poses a strong threat to the persistence of native assemblages in highly fluctuating environments. Therefore, conservation efforts to reduce native freshwater fish diversity loss in Mediterranean rivers should focus on mitigating the effect of invasive species and preventing future invasions

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The main purpose of this paper is building a research model to integrate the socioeconomic concept of social capital within intentional models of new firm creation. Nevertheless, some researchers have found cultural differences between countries and regions to have an effect on economic development. Therefore, a second objective of this study is exploring whether those cultural differences affect entrepreneurial cognitions. Research design and methodology: Two samples of last year university students from Spain and Taiwan are studied through an Entrepreneurial Intention Questionnaire (EIQ). Structural equation models (Partial Least Squares) are used to test the hypotheses. The possible existence of differences between both sub-samples is also empirically explored through a multigroup analysis. Main outcomes and results: The proposed model explains 54.5% of the variance in entrepreneurial intention. Besides, there are some significant differences between both subsamples that could be attributed to cultural diversity. Conclusions: This paper has shown the relevance of cognitive social capital in shaping individuals’ entrepreneurial intentions across different countries. Furthermore, it suggests that national culture could be shaping entrepreneurial perceptions, but not cognitive social capital. Therefore, both cognitive social capital and culture (made up essentially of values and beliefs), may act together to reinforce the entrepreneurial intention.

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Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression