The impact of integrated measurement errors on modeling long-run macroeconomic time series
研究了长期宏观经济数据中可能存在的综合测量误差（如英国1860-2012年数据）对双变量协整系统参数估计和检验的影响，发现当趋势或结构变化较大时，测量误差的影响较小。
Data spanning long time periods, such as that over 1860–2012 for the UK, seem likely to have substantial errors of measurement that may even be integrated of order one, but which are probably cointegrated for cognate variables. We analyze and simulate the impacts of such measurement errors on parameter estimates and tests in a bivariate cointegrated system with trends and location shifts which reflect the many major turbulent events that have occurred historically. When trends or shifts therein are large, cointegration analysis is not much affected by such measurement errors, leading to conventional stationary attenuation biases dependent on the measurement error variance, unlike the outcome when there are no offsetting shifts or trends.