Quantification of Qualitative Firm‐Level Survey Data
提出一种基于理论一致的程序来量化企业层面有序分类调查响应的方法，不假设阈值时间不变，应用于英国工业联合会数据表明其优于传统指标，对货币政策等经济决策有用。
Survey data are widely used to provide indicators of economic activity ahead of the publication of official data. This paper proposes an indicator based on a theoretically consistent procedure for quantifying firm-level survey responses that are ordered and categorical. Firms ’ survey responses are assumed to be triggered by a latent continuous random variable as it crosses thresholds. Breaking tradition these thresholds are not assumed time invariant. An application to firm-level survey data from the Confederation of British Industry shows that the proposed indicator of manufacturing output growth outperforms traditional indicators that assume time-invariant thresholds. Economic policy decisions, such as the management of monetary policy, require prompt and reliable economic information. Britain is one of the fastest countries at producing a quarterly estimate of real GDP growth; the first figures appear about twenty-seven days after the end of each quarter. However, such figures rely sub-stantially on forecasts (see Reed, 2000); estimates for manufacturing output cov-ering the whole quarter first become available only about thirty-eight days after the end of each quarter. Policy-makers are therefore keen to rely on data from a variety