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AN APPROACH TO IDENTIFYING AN OPTIMAL GUARANTEED BASIC INCOME

AN APPROACH TO IDENTIFYING AN OPTIMAL GUARANTEED BASIC INCOME. by Harvey Stevens for the 2018 NABIG Congress. THE CHALLENGE : WHICH OPTION IS THE BEST?. The Potential for an Optimum Design.

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AN APPROACH TO IDENTIFYING AN OPTIMAL GUARANTEED BASIC INCOME

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  1. AN APPROACH TO IDENTIFYING AN OPTIMAL GUARANTEED BASIC INCOME by Harvey Stevens for the 2018 NABIG Congress

  2. THE CHALLENGE: WHICH OPTION IS THE BEST?

  3. The Potential for an Optimum Design • The design of a GAI involves trade-offs due to the formula that determines the net benefit and cost: Net Benefit/Cost = Guarantee – (Other Income x Benefit Reduction Rate) • Given this formula, to remain within the same budget constraint, raising the value of the Guarantee (G) requires raising the Benefit Reduction Rate (BRR). • In turn, a higher G and a higher BRR generates the following trade-offs: • A reduction in the rate and depth of poverty; • A reduction in income inequality; • A reduction in labour supply and earnings; • Reduction in the number of winners. • To see the nature of these trade-offs, we can look at the previous chart of the four equal-cost options. • These trade-offs suggest that there may be an optimum combination of a G and BRR that maximizes poverty reduction while minimizing the loss of earnings and the number of winners.

  4. The Methodology for Determining an Optimal Design • Identify the criteria for assessing each G/BRR combination. With the SPSDM package, it is possible to measure the following: rate and depth of poverty/total poverty gap, degree of income inequality and the percent winners. By applying consensus estimates of substitution and income elasticities to the changes in marginal tax rates induced by the financing of the GAI and the G and BRR parameters, it is possible to estimate the change in earnings due to the GAI. • Measure each of the criteria under the current tax and transfer system. • Generate a range of equal cost G and BRR combinations and measure the criteria for each combination. • For each criteria and for each G and BRR combination, calculate the per cent change from the current system. The ‘per cent change’ calculation provides a common metric across the criteria. • Aggregate the per cent changes to create a total or average score for each combination. • Compare the aggregate score across the range of combinations to see if it reaches a maximum value. • If there is a maximum value , then that indicates the optimal design.

  5. An Example – Canada 2015

  6. A Second Example – Canada 2017

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