Measures of Technology and the Business Cycle
比较了生产函数法和结构VAR模型等多种技术度量方法，发现不同方法测度的技术高度相关，但识别假设的设定会影响结果，例如索洛残差呈强顺周期性，而其他度量则呈非周期性或逆周期性。
Empirical evidence on the relationship between technology shocks and e.g. hours worked hinges crucially on the identification of the unobservable technological progress. In this paper, we study different measures of technology in order to find out (i) to what extent they capture the same underlying phenomenon and (ii) whether the implications for macroeconomic theory are robust across the approaches. Several versions of the productions function approach and structural VAR models are investigated. Our main finding is that the different technology measures are highly correlated. However, the exact formulation of the identifying restrictions seems to matter for the results. While we replicate the standard finding of a strongly procyclical Solow residual, all other measures of technology are either acyclical or countercyclical.