Collaborative Research: Understanding the productivity of the world's most numerous firms: evidence from surveys and satellites

协作研究：了解世界上数量最多的公司的生产力：来自调查和卫星的证据

• 批准号: 1658740
• 负责人: Kyle Emerick
• 金额: $ 12.5万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1658740&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; productivity; world

Title: Understanding the productivity of the world's most numerous firms: evidence from surveys and satellitesWhy are some firms more productive than others? This has been a central question in economics for nearly a century, and its answer has implications for the long term well-being of societies, and for how government policy can promote this well-being. In this project we will study the most common firm type in the world: the family-owned farm. Our research focuses on farms in Africa, which employ a large share of the world?s poor. A detailed understanding the productivity of these firms -- whether and why some firms are more productive than others ? will help provide the foundation for designing policy interventions that could improve their overall productivity, and thus lift incomes for many of the world's poorest. Working with US satellite companies, we will also generate new estimates of agricultural productivity based on satellite imagery, and make these data available to both researchers and policymakers. Results from this research has policy implications for increasing the productivity of small businesses and thus reduce poverty throughout the world, including in the U.S. The goal of our proposed work is to characterize the size and sources of productivity dispersion across family owned farms, the most common firm type in the world and the employer of a majority of the world's poor. Productivity dispersion has been well studied among firms in the developed world, but surprisingly little is known about the temporal and spatial patterns of productivity dispersion in poor countries. Understanding the size and source of productivity gaps among agricultural firms -- previously difficult to study due to lack of data -- would fill a large gap in the existing productivity literature. We propose to make progress on this question by combining two newly-available sources of data: a growing set of high-quality household panel surveys currently underway by the World Bank in multiple African countries, and brand-new high-resolution satellite-based estimates of land productivity in Eastern Africa. These two data sources, in combination, will allow us to evaluate for agricultural firms the stylized facts that have been established for manufacturing and retail firms: whether productivity dispersion across firms is large and persistent, whether firm entry and exit are correlated with productivity, and whether selective exit and entry are an important source of aggregate productivity growth within the agricultural sector. Analysis will be conducted across nine African countries.

标题：了解世界上数量最多的公司的生产率：来自调查和卫星的证据为什么一些公司的生产率比其他公司高？近一个世纪以来，这一直是经济学中的一个核心问题，它的答案关系到社会的长期福祉，以及政府政策如何促进这种福祉。在这个项目中，我们将研究世界上最常见的企业类型：家庭农场。我们的研究重点是非洲的农场，那里雇佣了世界上很大的份额？S很穷。详细了解这些公司的生产率--一些公司是否以及为什么比其他公司的生产率更高？将有助于为设计政策干预措施提供基础，这些政策干预措施可以提高他们的整体生产率，从而提高世界上许多最贫穷者的收入。我们还将与美国卫星公司合作，根据卫星图像生成新的农业生产率估计，并将这些数据提供给研究人员和政策制定者。这项研究的结果对提高小企业的生产率从而减少世界各地的贫困具有政策含义，包括在美国。我们提议的工作的目标是描述家庭农场的生产力分散的规模和来源，家庭农场是世界上最常见的企业类型，也是世界上大多数穷人的雇主。在发达国家的企业中，生产率分散得到了很好的研究，但令人惊讶的是，人们对贫穷国家生产率分散的时间和空间模式知之甚少。了解农业企业生产率差距的大小和来源--以前由于缺乏数据而难以研究--将填补现有生产率文献中的一个巨大缺口。我们建议通过结合两个新的可用数据来源来在这个问题上取得进展：世界银行目前在多个非洲国家正在进行的越来越多的高质量家庭小组调查，以及全新的基于高分辨率卫星的东非土地生产力估计。这两个数据来源结合在一起，将使我们能够为农业公司评估已经为制造和零售公司建立的典型事实：公司之间的生产率分散是否巨大和持久，公司进入和退出是否与生产率相关，以及选择性退出和进入是否是农业部门总生产率增长的重要来源。分析将在九个非洲国家进行。