Business competition dynamics: agent-based modeling simulations of firms in search of economic performance

A intenção deste trabalho é explorar dinâmicas de competição por meio de “simulação baseada em agentes”. Apoiando-se em um crescente número de estudos no campo da estratégia e teoria das organizações que utilizam métodos de simulação, desenvolveu-se um modelo computacional para simular situações de competição entre empresas e observar a eficiência relativa dos métodos de busca de melhoria de desempenho teorizados. O estudo também explora possíveis explicações para a persistência de desempenho superior ou inferior das empresas, associados às condições de vantagem ou desvantagem competitiva

The art of being together: a social constructionist perspective on dialogic methods in the organizational context

The purpose of this project is to understand, under a social constructionist approach, what are the meanings that external facilitators and organizational members (sponsors) working with dialogic methods place on themselves and their work. Dialogic methods, with the objective of engaging groups in flows of conversations to envisage and co-create their own future, are growing fast within organizations as a means to achieve collective change. Sharing constructionist ideas about the possibility of multiple realities and language as constitutive of such realities, dialogue has turned into a promising way for transformation, especially in a macro context of constant change and increasing complexity, where traditional structures, relationships and forms of work are questioned. Research on the topic has mostly focused on specific methods or applications, with few attempts to study it in a broader sense. Also, despite the fact that dialogic methods work on the assumption that realities are socially constructed, few studies approach the topic from a social constructionist perspective, as a research methodology per se. Thus, while most existing research aims at explaining whether or how particular methods meet particular results, my intention is to explore the meanings sustaining these new forms of organizational practice. Data was collected through semi-structured interviews with 25 people working with dialogic methods: 11 facilitators and 14 sponsors, from 8 different organizations in Brazil. Firstly, the research findings indicate several contextual elements that seem to sustain the choices for dialogic methods. Within this context, there does not seem to be a clear or specific demand for dialogic methods, but a set of different motivations, objectives and focuses, bringing about several contrasts in the way participants name, describe and explain their experiences with such methods, including tensions on power relations, knowledge creation, identity and communication. Secondly, some central ideas or images were identified within such contrasts, pointing at both directions: dialogic methods as opportunities for the creation of new organizational realities (with images of a ‘door’ or a ‘flow’, for instance, which suggest that dialogic methods may open up the access to other perspectives and the creation of new realities); and dialogic methods as new instrumental mechanisms that seem to reproduce the traditional and non-dialogical forms of work and relationship. The individualistic tradition and its tendency for rational schematism - pointed out by social constructionist scholars as strong traditions in our Western Culture - could be observed in some participants’ accounts with the image of dialogic methods as a ‘gym’, for instance, in which dialogical – and idealized –‘abilities’ could be taught and trained, turning dialogue into a tool, rather than a means for transformation. As a conclusion, I discuss what the implications of such taken-for-granted assumptions may be, and offer some insights into dialogue (and dialogic methods) as ‘the art of being together’.

Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

A critical value function approach, with an application to persistent time-series

Researchers often rely on the t-statistic to make inference on parameters in statistical models. It is common practice to obtain critical values by simulation techniques. This paper proposes a novel numerical method to obtain an approximately similar test. This test rejects the null hypothesis when the test statistic islarger than a critical value function (CVF) of the data. We illustrate this procedure when regressors are highly persistent, a case in which commonly-used simulation methods encounter dificulties controlling size uniformly. Our approach works satisfactorily, controls size, and yields a test which outperforms the two other known similar tests.