| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP12523 |
| DP12523 Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria | |
| David McKenzie | |
| 发表日期 | 2017-12-21 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | We compare the relative performance of man and machine in being able to predict outcomes for entrants in a business plan competition in Nigeria. The first human predictions are business plan scores from judges, and the second are simple ad-hoc prediction models used by researchers. We compare these (out-of-sample) performances to those of three machine learning approaches. We find that i) business plan scores from judges are uncorrelated with business survival, employment, sales, or profits three years later; ii) a few key characteristics of entrepreneurs such as gender, age, ability, and business sector do have some predictive power for future outcomes; iii) modern machine learning methods do not offer noticeable improvements; iv) the overall predictive power of all approaches is very low, highlighting the fundamental difficulty of picking winners; and v) our models can do twice as well as random selection in identifying firms in the top tail of performance. |
| 主题 | Development Economics |
| 关键词 | entrepreneurship Machine learning Business plans Nigeria |
| URL | https://cepr.org/publications/dp12523 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/541334 |
| 推荐引用方式 GB/T 7714 | David McKenzie. DP12523 Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria. 2017. |
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