Welcome to our macroeconomic modelling tools database, a comprehensive resource that provides information on a range of tools used in the field of economics.
Our database includes various types of macroeconomic models, such as econometric models, general equilibrium models, dynamic stochastic general equilibrium models, and Input-Output models, each with their own unique features and advantages. The tools cover various aspects of macroeconomic modelling, including analysis of technological change, supply and demand shocks, and more.
We believe that our macroeconomic modelling tools database can serve as a valuable resource for researchers, policymakers, and other practitioners in the field of economics. Our database is a starting point for those who are seeking to explore the available macroeconomic modelling tools and to identify the most suitable one for their research or analysis.
While our database is not regularly updated, we welcome any contributions from users to help us improve and update the existing information. If you find that any information is missing or outdated, please feel free to contact us so that we can update the database accordingly.
Thank you for visiting our website, and we look forward to any feedback you may have to help us improve the resource further.
Type of Analysis
Two major categories of analysis are static and dynamic. Static model analyses the system state at one point of time. Dynamic models analyse system states at different point of times, which shows the varying behaviour vior of a model while moving from one state to another. There are also other more specific types such as comparative static, recursive dynamic and Intertemporal.
Type of model
Examples of model types are CGE, Macroeconometric and Input-output where each type has a different modelling g approach. For example, macroeconometric models use statistical techniques to provide economic forecasts while CGE are purely mathematical models that simultaneously solve a set of equations.
Developer
Identify the developer of the model, which can be an individual, institution, or consortium.
Number of Sectors/Activities
Indicates the number of sectors or activities that produce commodities and services in the economy.
Accessibility
Refers to the user’s type of accessibility to the software and/or data sources utilised in the tool. In some cases, one or more licenses are required to access the tool and sometimes it can be not accessible at all.
Supporting software
The supporting software is the platform where the model’s equations and variables are defined, and it is also where the model per se runs (e.g. MATLAB).
Spatial scale
Identify the geographical scale of the tool, which can be Global, National or Subnational.
Geographical coverage
The countries and regions that the model covers. For example, if the model is subnational for USA, there is geographical aggregation that is identified inside the model; rather than modelling every state individually, it divides the USA to three regions; South-West, North, and East.
Temporal scale
Specify the time duration during which the model runs (e.g., 1990-2050).
Technological change
Refers to the parameters and method (e.g. exogenous, endogenous) used to represent technological change in the economy.
Inclusion of modules
The macroeconomic model can have internal modules that represent some systems in the economy with extra details (e.g. Water-use or Emission trading).
Representation of labour/employment
Shows what kind of parameters and insights does the model use/produce in-line with the labour/employment representation in the economy. For example, some models can show the unemployment rate as a result of a new policy or technology.
Data Source
Most macroeconomic models depend heavily on input data that can be gathered from different sources such as public resources, national accounts, or established databases (e.g. European statistics). This dimension aims then to identify these data sources for each tool.
A. M. Elberry, R. Garaffa, A. Faaij, B. van der Zwaan, “A review of macroeconomic modelling tools for analysing industrial transformation,” Renewable and Sustainable Energy Reviews, vol. 199, p. 114462, 2024, doi: doi.org/10.1016/j.rser.2024.114462
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