Search results
1 – 10 of over 197000The concepts of complexity, endogeneity and circular causation – Myrdal's term was cumulative causation – are shown to be interrelated ones in configuring an economic model in the…
Abstract
Purpose
The concepts of complexity, endogeneity and circular causation – Myrdal's term was cumulative causation – are shown to be interrelated ones in configuring an economic model in the framework of systemic embedding and its empirical application.
Design/methodology/approach
The ensuing framework of economic modeling with complexity provides a controllable and predictable overarching worldview. Anomie in the economic universe and its embedded world‐system are analytically rejected. This consequence is due to the epistemic nature of modeling that combines complexity, endogeneity, and circular causation for attaining predictability and controllability, even in the face of complex systemic perturbations. The epistemology of unity of knowledge contrasted with rationalism is treated as the foundational worldview. An illustrative empirical work is given to convey the conceptual model and its applied viability.
Findings
Both the theoretical and empirical results point out how the induced effects of knowledge flows in reference to the epistemology of unity of knowledge continuously improves the complementary relationships of the evolutionary learning fields, and rejects marginalism as being logically non‐sequiter in such epistemic systems.
Research limitations/implications
More variables and data would increase the explanation of the continuous simulation in the evolutionary learning world‐system model.
Practical implications
More data would increase the versatility of the empirical exercise.
Social implications
The study is based on the idea of social and economic interface in extending the scope of economic modeling.
Originality/value
The paper is very original in the area of heterodox economics that questions orthodox economic postulates and presents the complex methodology by circular causation method instead.
Details
Keywords
Input‐output modeling can accurately forecast the benefits associated with corporate real estate projects. This paper aims to address the economic and employment impact analysis…
Abstract
Purpose
Input‐output modeling can accurately forecast the benefits associated with corporate real estate projects. This paper aims to address the economic and employment impact analysis practices used in input‐output modeling and identifies resources for corporate real estate executives when working with community groups and public officials. By understanding this topic, corporate real estate executives can more effectively demonstrate the value of corporate activities to a community. An impact analysis case study is presented that includes an example of economic impact report content. Input‐output modeling is an effective analytical tool for corporate real estate site selection, facilities expansion, and other community relations projects. This study addresses the major issues in corporate/community relationships and focuses on the corporate need to demonstrate project contributions to community economic vitality. As political, special interest, and public views about business expansion and development harden, corporate real estate executives and specialists need to utilize effective tools to balance the debate.
Design/methodology/approach
This study presents a review of input‐output economic modeling techniques, application of the model, key terms, a case study of a $2.1 billion expansion project, and a sample outline of an impact analysis report. This approach provides a good conceptual framework, terms, and the application of an economic and employment impact approach to measuring the total contribution of corporate real estate activities in a community or region.
Findings
Demonstrates methods measuring economic and employment multipliers resulting from direct, indirect, and induced corporate project impacts. The findings will assist professionals responsible for corporate/community relations by enhancing their understanding of economic impacts.
Originality/value
This paper presents an overview of an effective modeling technique that can be used to accurately estimate the community economic and employment contributions resulting from a new corporate real estate project. Emerging corporate/community relations issues are discussed and resources are identified.
Details
Keywords
Traditionally, economic production models consider pollution as bads that may be modeled as either outputs or inputs in economic models. The purpose of this paper is to examine…
Abstract
Purpose
Traditionally, economic production models consider pollution as bads that may be modeled as either outputs or inputs in economic models. The purpose of this paper is to examine the implications of these modeling choices on the measurements of productive efficiency and private costs of pollution control.
Design/methodology/approach
The authors apply the hyperbolic distance functions to measure trucking efficiency and the private costs of pollution control.
Findings
The results show: (i) regardless of the choice of modeling, when only one bad was incorporated in hyperbolic distance functions, the efficiency loss and private abatement cost measures derived from the two models were equivalent, but potential pollution reduction and good output expansion differed; (ii) when more than one bad were introduced, the equivalence of efficiency loss measure in (i) did not hold; and (iii) the potential amounts of pollution reduction and good output expansion were larger when bads were modeled as inputs. With multiple bads, private abatement costs varied considerably under the two modeling treatments.
Practical implications
From a policy standpoint, the results suggest that one should consider the modeling options with caution when multiple economic bads are involved, because the resulting measures of economic burden of pollution control differ.
Originality/value
The paper shows that the traditional conceptual framework for modeling pollution in hyperbolic distance functions could yield inconsistent results.
Details
Keywords
During the last decade or so, philosophers of science have shown increasing interest in scientific models and modeling. The primary impetus seems to have come from the philosophy…
Abstract
During the last decade or so, philosophers of science have shown increasing interest in scientific models and modeling. The primary impetus seems to have come from the philosophy of biology, but increasingly the philosophy of economics has been drawn into the discussion. This paper will focus on the particular subset of this literature that emphasizes the difference between a scientific model being explanatory and one that provides explanations of specific events. The main differences are in the structure of the models and the characteristics of the explanatory target. Traditionally, scientific explanations have been framed in terms of explaining particular events, but many scientific models have targets that are hypothetical patterns: “patterns of macroscopic behavior across systems that are heterogeneous at smaller scales” (Batterman & Rice, 2014, p. 349). The models with this characteristic are often highly idealized, and have complex and heterogeneous targets; such models are “central to a kind of modeling that is widely used in biology and economics” (Rohwer & Rice, 2013, p. 335). This paper has three main goals: (i) to discuss the literature on such models in the philosophy of biology, (ii) to show that certain economic phenomena possess the same degree of heterogeneity and complexity often encountered in biology (and thus, that hypothetical pattern explanations may be appropriate in certain areas of economics), and (iii) to demonstrate that Hayek’s arguments about “pattern predictions” and “explanations of the principle” are essentially arguments for the importance of this type of modeling in economics.
Details
Keywords
The three-sector framework (relating to agriculture, manufacturing and services) is one of the major concepts for studying the long-run change of the economic structure. This…
Abstract
Purpose
The three-sector framework (relating to agriculture, manufacturing and services) is one of the major concepts for studying the long-run change of the economic structure. This paper aims to discuss the system-theoretical classification of the structural change in the three-sector framework and, in particular, its predictability by the Poincaré–Bendixson theory.
Design/methodology/approach
This study compares the assumptions of the Poincaré–Bendixson theory to the typical axioms of structural change modeling, the empirical evidence on the geometrical properties of structural change trajectories and the methodological arguments referring to the laws of structural change.
Findings
The findings support the assumption that the structural change phenomenon is representable by a dynamical system that is predictable by the Poincaré–Bendixson theory. This result implies, among others, that in the long run, structural change is either transitory or cyclical and can be used in further geometrical/topological long-run structural change modeling and prediction.
Originality/value
Although widespread in mathematics, geometrical/topological modeling methods have not been used in modeling and prediction of long-run structural change, despite the fact that they seem to be predestined for this purpose owing to their global, system-theoretical nature, allowing for a reduction of ideology content of predictions and greater robustness of results.
Details
Keywords
Frank Messner, Hagen Koch and Michael Kaltofen
In this chapter it is shown how economic evaluation algorithms of water use can be integrated into a long-term water management model such that surface-water availability and…
Abstract
In this chapter it is shown how economic evaluation algorithms of water use can be integrated into a long-term water management model such that surface-water availability and economic evaluation of various levels of water availability to different uses can be modeled simultaneously. This approach makes it possible to include essential features of economic analyses of water use into water resource modeling and thus improves the capability of such models to support decision making in water management. This is especially relevant for the implementation of the Water Framework Directive, which requires economic analyses to be included in the decision process about future water management strategies.
The water management simulation model WBalMo is presented and the integration of economic-evaluation algorithms is demonstrated for the examples of surface-water use for fish farming and for filling open-cast mining pits in order to achieve acceptable water-quality levels in the emerging pit lakes. Results of applying this integrated evaluation approach are shown for different water management scenarios under conditions of global change in the East German Spree and Schwarze Elster river basins, where water scarcity is an urgent issue. Among the lessons which are drawn by the authors one lesson reads that integrating economic evaluation algorithms into a pre-existing model might bring enormous problems. Therefore, such model approaches should be developed together by water engineers and economists in an interdisciplinary endeavor right from the start.