Abstract
AbstractThis paper examines the impact of Alaska’s Permanent Fund Dividend on crime. The Dividend has been payable annually to state residents since 1982 and is the world’s longest-running example of a basic income. Initially universal, from 1989 onwards eligibility was withdrawn from an increasing proportion of those in prison. A Bayesian structural time series estimator is used to simulate Alaskan crime rates in the counterfactual no-Dividend case. A comparison with actual rates provides an estimate of the Dividend’s impact. This does not provide strong evidence of an effect. However, incorporating information on Dividend amounts suggests the size of payments is important, with larger amounts reducing crime. There is no evidence that this effect is reinforced by the 1989 change to eligibility. The results demonstrate the potential for a basic income to encourage positive outcomes and lend support to payment being universal rather than conditional.
Highlights
The idea of a universal basic income is certainly not new (More 1516 [1963]) but recent years have seen increased interest. Sloman (2018) identifies the current decade as representing the latest distinct wave of enthusiasm for the concept
Since the Dividend is Dorsett not paid in any states other than Alaska, the expectation is that any suggestion of an impact from these placebo impulse response functions (IRFs) should only ever arise chance
This paper has examined the impact of Alaska’s Permanent Fund Dividend on crime
Summary
The idea of a universal basic income is certainly not new (More 1516 [1963]) but recent years have seen increased interest. Sloman (2018) identifies the current decade as representing the latest distinct wave of enthusiasm for the concept. BSTS adopts a Bayesian approach, constructing multiple synthetic controls based on draws from the posterior distribution of simulated coefficients over the post-intervention period Each such synthetic control provides counterfactual outcomes which can be subtracted from the observed outcomes in the treated unit to give a distribution of simulated impacts, each with draw-specific time series properties. This feature is useful in this study where it is exploited to examine how impacts vary year-on-year with changes in the size of the Dividend. Counterfactual outcomes under BSTS resemble true outcomes more closely in the pre-Dividend years than is the case for the synthetic control approach; for property crime, the RMSEs are 3.8% and 7.8% respectively.
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