If a policy change causes a Pareto improvement, is the outcome necessarily Pareto efficient if a policy change causes a Pareto improvement, then the outcome is not necessarily Pareto efficient this is because another change in the policy could cause another Pareto improvement.
A Pareto development is a development of a device whilst an alternative in the allocation of goods harms no person and advantages as a minimum one character. Pareto enhancements also are called "no-brainers" and are generally predicted to be rare, due to the plain and effective incentive to make any available Pareto development.
Factors that lie within the PPF display an inefficient or below-usage of resources – this is Pareto inefficient. A Pareto development way that output of both products can increase as we move from inside the PPF to factors at the PPF boundary.
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If a retailer needed help with store design and training sales personnel, it would most likely use the services of a full-service wholesaler.
A service is "an act or use for which a consumer, commercial enterprise, or authorities is inclined to pay." Examples include paintings by way of hairdressers, medical doctors, lawyers, mechanics, banks, coverage organizations, and many others. Public offerings are paid for by society as a whole.
Lively occupation or role. b : Employment as a servant has started. 2a : work finished with the aid of good humans. b : assist, use, use like helping.
A service is a pastime or overall performance that constitutes a suggestion to any other individual this is intangible in nature and does now not bring about any possession. ”
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Answer:
The answer is C.It makes recommendations that are validated using machine learning.
Explanation:
A performance planner is a tool used by Google Ads to devise plans in relation to how a business spends on advertising and how changes on advertisement campaigns will affect key metrics and the general performance. It is mostly used as a forecasting tool, with the use of machine learning to show the possibilities or potential outcomes in Google Ads campaigns. This implies that all the conclusions arrived at, are determined by machine learning.
E
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