Downloads provided by UsageCounts
doi: 10.1257/aer.20151233
Blum, Claro, and Horstmann (2016) make two statements about the balls-and-bins model of Armenter and Koren (2014). First, that using firm-level shipment data changes some of our results. Second, that the balls-and-bins model is not an appropriate statistical method. We respond to the first statement and argue that the second statement is unfounded and unrelated to the first. Indeed, the work of Blum, Claro, and Horstmann (2016) is a perfect example of how to use balls-and-bins in a rich dataset to spot interesting data patterns. (JEL F11, F14)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 5 | |
| downloads | 12 |

Views provided by UsageCounts
Downloads provided by UsageCounts