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In modern economic literature, the most common measure of a taxpayer's loss from a distortionary tax, such as a tax on bicycles, is the equivalent variation, the maximum amount that a taxpayer would be willing to forgo in a lump sum to avoid the tax. The deadweight loss can then be interpreted as the difference between the equivalent variation ...
Otherwise, it is called unbalanced assignment. [1] If the total cost of the assignment for all tasks is equal to the sum of the costs for each agent (or the sum of the costs for each task, which is the same thing in this case), then the problem is called linear assignment.
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There are several open source projects that provide similar data version control capabilities to DVC, [52] such as: Git LFS, Dolt, Nessie, and lakeFS. These projects vary in their fit to the different needs of data engineers and data scientists such as: scalability, supported file formats, support in tabular data and unstructured data, volume ...
A chained volume series is a series of economic data (such as GDP, GNP or similar kinds of data) from successive years, put in real (or constant, i.e. inflation- and deflation-adjusted) terms by computing the aggregate value of the measure (e.g. GDP or GNP) for each year using the prices of the preceding year, and then 'chain linking' the data together to obtain a time-series of figures from ...
A common position in economics is that the costs in a cost-benefit analysis for any tax-funded project should be increased according to the marginal cost of funds, because that is close to the deadweight loss that will be experienced if the project is added to the budget, or to the deadweight loss removed if the project is removed from the budget.
Computational tools for economics include a variety of computer software that facilitate the execution of various matrix operations (e.g. matrix inversion) and the solution of systems of linear and nonlinear equations. Various programming languages are utilized in economic research for the purpose of data analytics and modeling.
While open data may theoretically have a low production cost, the cost of creating the original data set as well as maintaining that data once it is produced can be expensive. [1] Though the creation of data may be expensive governments around the world such as France, the United States, and Japan, are anticipating substantial economic growth.