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Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method
Population Research and Policy Review ( IF 1.899 ) Pub Date : 2021-03-22 , DOI: 10.1007/s11113-021-09646-7
Jeff Tayman , David A. Swanson , Jack Baker

Tayman and Swanson (J Popul Res 34(3):209–231, 2017) found in Washington State counties that a forecast based on the Hamilton–Perry method using a synthetic adjustment (SYN) of cohort change ratios and child-woman ratios had greater accuracy and less bias compared to forecasts holding these ratios constant (CONST). In this paper, we assess the robustness of SYN’s efficacy by evaluating forecast accuracy, bias, and distributional error across age groups in counties nationwide. We also investigate whether forecast errors and their patterns change for SYN and CONST if forecasts by age and gender are adjusted to an independent total population forecast for each county. Our main findings are as follows: (1) SYN lowers forecast error compared to CONST whether the forecasts are controlled or not; (2) controlling also leads to the improvements in forecast error, often exceeding those in SYN; and (3) using SYN and controlling together has the greatest effect in reducing forecast error. These findings remain after controlling for population size and growth rate, but the positive impacts on forecast error of SYN and controlling are most evident in counties with less than 30,000 population and that grow by 15% or more.



中文翻译:

使用综合调整和控制方法从汉密尔顿-佩里方法改进郡县人口预测

Tayman和Swanson(J Popul Res 34(3):209–231,2017)在华盛顿州各县发现,基于汉密尔顿-佩里方法的预测使用了队列变化率和男女比例的综合调整(SYN),与保持这些比率恒定(CONST)的预测相比,准确性更高,偏差更小。在本文中,我们通过评估全国各县不同年龄组的预测准确性,偏倚和分布误差来评估SYN效力的稳健性。如果将按年龄和性别进行的预测调整为每个县的独立总人口预测,我们还将调查SYN和CONST的预测误差及其模式是否会发生变化。我们的主要发现如下:(1)无论预测是否受控,SYN都比CONST降低了预测误差;(2)控制还导致预测误差的改善,通常超过了SYN中的预测误差;(3)同时使用SYN和控制可以最大程度地减少预测误差。在控制了人口规模和增长率之后,这些发现仍然存在,但是在人口少于30,000且增长15%或更多的县中,对SYN预测误差和控制的正面影响最为明显。

更新日期:2021-03-23
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