4,040 research outputs found
Another look at the estimation of dynamic programming models with censored decision variables
In this paper we propose a new approach to estimate the structural parameters in the context of a censored continuous decision model. Instead of handling with the original model, we consider an approximate model in which the decision variable has been discretized in a finite number of values. In this sense, an ordered choice model becomes a natural approximation to an underlying and more complicated censored continuous one. We extend the kind of Hotz-Miller estimators proposed for the estimation of binary or multinomial choice models to the context of ordered choice models. The estimation approach is based on the existence of a one-to-one mapping from conditional choice value functions to conditional choice probabilities. Exploiting the invertibility of that mapping it is possible to obtain structural parameter estimates without solving the dynamic programming problem
Pseudo-maximum likelihood estimation of a dynamic structural investment model
This paper belongs to the recent investment literature focused on the modelling of microeconomic investment decisions. The increasing concern about this topic is related to the growing availability of microeconomic datasets which show the investment behavior taking place at the firm level. This behavior is far from the smooth capital adjustment pattern derived from the traditional investment models. Rather it is characterized by infrequent and lumpy adjustment. New investment models must be considered to capture this behavior. In this paper we formulate a dynamic structural investment model with irreversibility and nonconvex adjustment costs and try to stress the importance of these costs in the firms' investment decisions. From the methodological point of view, we set the investment decision on the dynamic programming framework. More specifically, we consider a discrete choice dynamic programming problem in which firms decide to invest or not to invest. The estimation strategy we adopt is the Nested Pseudo-Likelihood (NPL) algorithm recently proposed by Aguirregabiria and Mira (2002). It is an estimation method which has clear advantages over previous techniques proposed in this context. Up to our knowledge, this paper constitutes the first empirical application of this estimation method
Estimation of a dynamic discrete choice model of irreversible investment
In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem
ESTIMATION OF A DYNAMIC DISCRETE CHOICE MODEL OF IRREVERSIBLE INVESTMENT
In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem.
ANOTHER LOOK AT THE ESTIMATION OF DYNAMIC PROGRAMMING MODELS WITH CENSORED DECISION VARIABLES
In this paper we propose a new approach to estimate the structural parameters in the context of a censored continuous decision model. Instead of handling with the original model, we consider an approximate model in which the decision variable has been discretized in a finite number of values. In this sense, an ordered choice model becomes a natural approximation to an underlying and more complicated censored continuous one. We extend the kind of Hotz-Miller estimators proposed for the estimation of binary or multinomial choice models to the context of ordered choice models. The estimation approach is based on the existence of a one-to-one mapping from conditional choice value functions to conditional choice probabilities. Exploiting the invertibility of that mapping it is possible to obtain structural parameter estimates without solving the dynamic programming problem.
GMM estimation of a production function with panel data : an application to Spanish manufacturing firms
In this paper we consider the estimation of a Cobb-Douglas production function using a panel dataset of Spanish manufacturing firms. As it is stressed in the econometric literature, the use of standard GMM first differences estimators to eliminate the unobserved firm-specific effects may yield imprecise estimates, particularly in the case of the estimation of the production function. The reason is that the high persistence of output and inputs involved in the estimation of production functions make that their lagged levels to be weak instruments for the first differences of these series. The extended GMM estimator proposed by Arellano and Bover (1995) considers further orthogonality conditions based on lagged differences as instruments for the equation in levels. This approach has been applied to the estimation of technological parameters by Blundell and Bond (1999). Our estimation results, based on this approach, confirm the better performance of the extended GMM estimator compared to the standard first-differenced GMM estimato
Investigation on the structural and magnetic properties of sputtered TbFe2/Fe3Ga heterostructures
We have analyzed the structural and magnetic properties of as-grown and annealed [TbFe2/Fe3Ga]n heterostructures grown by sputtering. Evidence of the bcc structure in the Fe3Ga layers has been found. The diffraction peak related to this structure shifts to high angles with the annealing temperature. Also, we have observed a change in the microstructure of the Tb-Fe layers when the thickness layer is reduced in the as-grown heterostructures. Moreover, the Tb content is lower than 33% of the TbFe2 Laves phase and it depends on the layer thickness. The thermal treatments promote the increase of the Tb content, but only in the heterostructures with thick layers. The strong lattice mismatch between the Tb-Fe and Fe-Ga layers seems to prevent a complete Tb diffusion upon the annealing process. Thus, the crystallization of the TbFe2 Laves phase is inhibited in the heterostructures with thin layers, although our experimental results indicate the presence of potential magnetostrictive TbFeGa alloy
GMM ESTIMATION OF A PRODUCTION FUNCTION WITH PANEL DATA: AN APPLICATION TO SPANISH MANUFACTURING FIRMS
In this paper we consider the estimation of a Cobb-Douglas production function using a panel dataset of Spanish manufacturing firms. As it is stressed in the econometric literature, the use of standard GMM first differences estimators to eliminate the unobserved firm-specific effects may yield imprecise estimates, particularly in the case of the estimation of the production function. The reason is that the high persistence of output and inputs involved in the estimation of production functions make that their lagged levels to be weak instruments for the first differences of these series. The extended GMM estimator proposed by Arellano and Bover (1995) considers further orthogonality conditions based on lagged differences as instruments for the equation in levels. This approach has been applied to the estimation of technological parameters by Blundell and Bond (1999). Our estimation results, based on this approach, confirm the better performance of the extended GMM estimator compared to the standard first-differenced GMM estimator
La mĂșsica en su contribuciĂłn al desarrollo de la inteligencia emocional en educaciĂłn infantil
Treball final de Grau en Mestre o Mestra d'EducaciĂł Infantil. Codi: MI1040. Curs acadĂšmic 2016-2017En este trabajo de investigaciĂłn de final de grado en maestra de educaciĂłn infantil se pretende demostrar la importancia de la mĂșsica para el correcto desarrollo emocional del alumnado de infantil. Partiendo de la definiciĂłn de educaciĂłn emocional y de la importancia de trabajarla en educaciĂłn, nos centraremos en la contribuciĂłn que puede hacer la mĂșsica en el desarrollo del ĂĄmbito emocional en las aulas.
En este trabajo, que consistirĂĄ en la creaciĂłn de una propuesta didĂĄctica, se experimentarĂĄn 4 emociones de las que considera Ekman como bĂĄsicas, que serĂĄn: la alegrĂa, la tristeza, el miedo y la ira/rabia. Para conseguir este objetivo utilizaremos una metodologĂa activa i participativa que tenga como base el juego. Y que consista en actividades orientadas a que los niños conozcan las emociones, para que asĂ se puedan trabajar estas emociones teniendo como elemento comĂșn, en la mayorĂa de ellas, la mĂșsica.
Me centrare en el trabajo de las emociones båsicas ya que son las que se dan con mayor frecuencia en la vida cotidiana de los niños y niñas de infantil y las que se trabajan mås a menudo en las aulas. Por eso los niños y niñas deben tener un conocimiento y una gestión, de estas, correcta para su buen desarrollo emocional y contribuir con ello al desarrollo integral de su persona
Del salterio al marial: sobre las fuentes de las imĂĄgenes de los CĂłdices de las Historias de las Cantigas de Santa MarĂa
El presente trabajo pretende ofrecer una reflexiĂłn sobre el concepto de
âfuenteâ aplicado al estudio de las versiones figuradas de las Cantigas de Santa MarĂa en los
Códices de las Historias. Después de dibujar un breve panorama historiogråfico se propone
una nueva aproximaciĂłn utilizando como base teĂłrica la distinciĂłn genĂ©rica entre composiciones lĂricas y narrativas en verso, dos modos que exigen retĂłricas visuales diferentes,
y que determinĂł el uso de fuentes especĂficas en cada casoThe aim of this paper is to offer a reflection on the concept of âsourceâ as applied
to the study of the miniatures of the Cantigas de Santa MarĂa in the CĂłdices de las Historias. After taking a brief look at the historiographic scene, we propose a new approach
based on the distinction between lyrical and narrative verse. These are different genres
that require different visual manifestations and, for each, specific sources had to be used
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