The effects of institutional and technological change and business cycle fluctiations on seasonal patterns in quarterly industrial production series

Changes in the seasonal patterns of macroeconomic time series may be due to the effects of business cycle fluctuations or to technological and institutional change or both. We examine the relative importance of these two sources of change in seasonality for industrial production series of the G7 countries. We find compelling evidence that the effects of gradual institutional and technological change are much more important than the effects attributable to the business cycle

Smooth transition autoregressive models - A survey of recent developments

This paper surveys recent developments related to the smooth transition autoregressive [STAR] time series model and several of its variants. We put emphasis on new methods for testing for STAR nonlinearity, model evaluation, and forecasting. Several useful extensions of the basic STAR model, which concern multiple regimes, time-varying nonlinear properties, and models for vector time series, are also reviewed

A Novel Forecasting Model for the Baltic Dry Index Utilizing Optimal Squeezing

Marine transport has grown rapidly as the result of globalization and sustainable world growth rates. Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian compressed regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the BDI with considerable success

Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]., Oxford University Press.

Tertulias matemáticas dialógicas para el aprendizaje de las matemáticas en mujeres adultas no escolarizadas y sin titulación académica

[spa] Esta investigación se enmarca en el Objetivo 4 de la agenda internacional para el Desarrollo Sostenible 2030: Garantizar una educación inclusiva, equitativa y de calidad y promover oportunidades de aprendizaje durante toda la vida para todos (ONU, 2020). Las metas y esfuerzos globales que subyacen a este objetivo otorgan especial atención a la inclusión educativa de las mujeres ya que son ellas quienes continúan afrontando mayores barreras de participación y desarrollo derivadas de las múltiples condiciones de desigualdades que persisten. Ante este panorama, la comunidad científica internacional ha identificado Actuación Educativa de Éxito (AEE) (Flecha, 2015) que contribuyen a la inclusión social desde la educación. Una de estas AEE son las Tertulias Matemáticas Dialógicas (TMD) (Díez-Palomar, 2017) que consisten en la construcción colectiva de significados en torno a la lectura dialógica de una obra clásica en el campo de las matemáticas. Esta investigación se enfoca en la forma en cómo las TMD contribuyen en la inclusión educativa y empoderamiento para el uso crítico de las matemáticas de las mujeres adultas que no están escolarizadas y que no cuentan con titulación académica. Siguiendo el enfoque de la Metodología Comunicativa de investigación, se desarrollaron técnicas de recogida de información de corte cualitativo para el estudio de dos casos: uno en la Ciudad de México y otro en Barcelona. En ambas TMD participaban mujeres de distintas edades y procedentes de contextos diversos. Los hallazgos dan cuenta del impacto positivo de las TMD en dos dimensiones del aprendizaje de las matemáticas: actitudinal e instrumental. El funcionamiento de las TMD basado en el aprendizaje dialógico y la participación igualitaria de las mujeres, incidió en la superación de actitudes y concepciones negativas en torno a las matemáticas. Las interacciones establecidas en las TMD permitieron que las participantes transformaran el auto concepto de sí mismas sobre el aprendizaje, resignificaran el valor de las matemáticas en sus vidas y se empoderaran en el uso crítico de esta ciencia en su vida cotidiana. Así mismo, se manifestaron mejoras en competencias matemáticas de interpretación, formulación, uso de lenguaje matemático, representación y visualización matemática y reflexión y acción crítica en la resolución de problemas. Finalmente, la investigación también logra constatar un efecto en la motivación de las participantes por reincorporarse a la vida académica y promover el aprendizaje de las matemáticas en sus entonos inmediatos. Estos hallazgos pretenden motivar investigaciones más amplias e impulsar el interés científicos sobre las actuaciones educativas de enfoque comunitario que permiten la inclusión de las mujeres adultas que, por razones diversas, se encuentran excluidas de la educación y sin oportunidades valiosas de aprendizaje a lo largo de sus vidas.[eng] This research is framed on Objective 4 of the international agenda for Sustainable Development 2030: Guarantee inclusive, equitable and quality education and promote lifelong learning opportunities for all (UN, 2020). The global goals and efforts that underlie this objective pay special attention to the educational inclusion of women since they still face greater barriers to participation and development derived from the multiple and persistent inequalities. The international scientific community has identified Successful Educational Action (SEA´s) (Flecha, 2015) that contribute to social inclusion from education. One of these is Dialogic Mathematics Gatherings (DMG) (Díez-Palomar, 2017) that consist of collective meaning constructions around the dialogical reading of a classic work in the field of mathematics. This research focuses on how DMGs contribute to the educational inclusion and empowerment for critical use of mathematics by non-academic women. Following the Communicative Research Methodology approach, qualitative information collection techniques were developed for the study of two cases: one in Mexico City and the other in Barcelona. In both cases women from different ages and contexts were involved. Findings account for the positive impact of DMG on two mathematics learning dimensions: attitudes and skills. The functioning of the DMG based on dialogic learning and equal participation of women, influenced the overcoming of negative attitudes and misconceptions about mathematics. The interactions established allowed the participants to transform their self-concept of learning and create a new meaning about the value of mathematics in their lives. Likewise, improvements were manifested in mathematical skills and competencies as wells as: interpretation, formulation, use of mathematical language, representation and mathematical visualization, and reflection and critical action in solving problems. Finally, the research also shows an effect on the motivation of the participants to rejoin the academic life and promote the learning of mathematics in their context. These findings are intended to motivate broader research and boost scientific interest in community-based educational actions that allow the inclusion of adult women who are excluded from education and without valuable learning opportunities throughout their lives

Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models.

During the past few years investigators have found evidence indicating that various time-series representing business cycles, such as production and unemployment, may be nonlinear. In this paper it is assumed that if the time-series is nonlinear, then it can be adequately described by a smooth transition autoregressive (STAR) model. The paper describes the application of these models to quarterly logarithmic production indices for 13 countries and "Europe." Tests reject linearity for most of these series, and estimated.STAR models indicate that the nonlinearity is needed mainly to describe the responses of production to large negative shocks such as oil price shocks. Copyright 1992 by John Wiley & Sons, Ltd.