Quantification of Qualitative Firm‐Level Survey Data
Bibliographic Data
| ID | 9950100 |
|---|---|
| Authors | James Mitchell (0000-0003-0532-4568, National Institute of Economic and Social Research), Richard J Smith (0000-0002-6340-0656, University of Bristol and National Institute of Economic and Social Research), Martin Weale (0000-0002-2016-0437, National Institute of Economic and Social Research), Martin R Weale (National Institute of Economic and Social Research) |
| Year | 2002 |
| Volume | 112 |
| Issue | 478 |
| Pages | C117-C135 |
| Publication date | 2002-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Economic Journal (JOURNAL) |
| Journal identifiers | ISSN: 0013-0133 • E-ISSN: 1468-0297 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1111/1468-0297.00021 |
| OpenAlex | W2008760988 |
| Language | EN |
| Citations received | 3 |
| References cited | 11 |
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
Business · Categorical variable · Econometrics · Economics · Industrial organization · Invariant (physics · Statistics · Survey data collection · Computer Science · Economic, financial, and policy analysis · Efficiency Analysis Using DEA · Mathematics · Monetary Policy and Economic Impact
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,15 |
| Citation span | 2006 - 2018 (13) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 3 |