Identification of technology shocks using misspecified VARs
本文提出一种方法，减少因VAR模型滞后结构误设导致的长程限制识别偏差，模拟显示该方法优于多种替代方案，应用于美国数据发现人均工时对技术冲击呈正向驼峰响应。
Abstract Studies that evaluate the effects of technology shocks often employ structural VARs identified with long‐run restrictions. In the presence of a mismatch between the lag structures of the true data‐generating process and the adopted VAR, estimates based on long‐run restrictions can be biased. This paper offers a method that can reduce this bias substantially. Using artificial data, I assess the performance of the proposed method and find that it can outperform a range of alternative procedures. Applying the procedure to the US data, I find that per‐capita hours exhibit a positive hump‐shaped response profile in response to a technology shock.