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IMMIGRATION, ENDOGENOUS SKILL BIAS OF TECHNOLOGICAL CHANGE, AND WELFARE ANALYSIS
Macroeconomic Dynamics ( IF 0.7 ) Pub Date : 2020-12-01 , DOI: 10.1017/s1365100520000553
Gonca Senel

This paper investigates the long-run effects of immigration on wages and welfare in a model with endogenous technology choice (ETC) where firms are allowed to choose their optimal skill intensity from a menu of available technologies. I embed the ETC framework into the Auerbach and Kotlikoff model (1987) that features a large set of overlapping generations, a rich collection of population dynamics, and a social security system. I calibrate the model to match with the U.S. data and evaluate the effect of ETC with the help of two experiments. In the first experiment, I increase the share of high-skilled immigrants and compare the wage and welfare predictions of the model with ETC to a standard model where the skill intensities in production technology are fixed. In the standard model, since the skill intensities are constant, increase in the supply of high-skilled labor leads to a decrease in high-skilled wages and an increase in low-skilled wages. On the other hand, in the model with ETC, negative supply-side effects are counterbalanced by an increase in the intensity of the more abundant high-skilled labor, leading to a smaller decrease in their wages. The discrepancy between wage predictions of these two models is also reflected in the welfare: while the model with ETC predicts an increase in both high- and low-skilled natives’ welfare, the standard model would predict a decrease in the welfare of the high skilled and a larger increase in the welfare of the low skilled. In the second experiment, I examine the effects of an increase in low-skilled immigration and find that in this case, since the initial production technology is low-skilled intensive, the ETC effects are smaller. These results imply that if ETC is ignored, both in the short run and long run, wage and welfare analyses of immigration will be incomplete, and even misleading.



中文翻译:

移民、技术变革的内生技能偏差和福利分析

本文在具有内生技术选择 (ETC) 的模型中研究了移民对工资和福利的长期影响,其中允许公司从可用技术菜单中选择其最佳技能强度。我将 ETC 框架嵌入到 Auerbach 和 Kotlikoff 模型 (1987) 中,该模型具有大量重叠的世代、丰富的人口动态集合和社会保障体系。我校准模型以匹配美国数据,并在两个实验的帮助下评估 ETC 的效果。在第一个实验中,我增加了高技能移民的比例,并将 ETC 模型的工资和福利预测与生产技术中的技能强度固定的标准模型进行了比较。在标准模型中,由于技能强度是恒定的,高技能劳动力供给的增加导致高技能工资下降,低技能工资增加。另一方面,在具有 ETC 的模型中,负供给侧效应被更丰富的高技能劳动力的强度增加所抵消,导致他们的工资下降幅度较小。这两个模型的工资预测之间的差异也反映在福利上:虽然 ETC 模型预测高技能和低技能原住民的福利都会增加,但标准模型会预测高技能的福利会减少低技能人员的福利也有较大的增加。在第二个实验中,我检查了低技能移民增加的影响,发现在这种情况下,由于最初的生产技术是低技能密集型的,ETC 影响较小。这些结果表明,如果忽略 ETC,无论从短期还是长期来看,移民的工资和福利分析都将是不完整的,甚至会产生误导。

更新日期:2020-12-01
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