Climate, agriculture, and economic development : theories and methods for agricultural productivity analysis
Abstract/Contents
- Abstract
- Increasing agricultural productivity is a cornerstone of the global sustainable development agenda. Using resources more efficiently can reduce the environmental impacts of food systems and create economic opportunities for the world's poor, the majority of whom earn their living from agriculture. However, there remain fundamental uncertainties about how to effectively direct investments for agricultural development, and the role agricultural productivity growth plays in economic development more generally. One key source of uncertainty is global climate change, which is predicted to disproportionately affect agriculture in developing countries. In my dissertation, I investigate the relationship between climate, agricultural productivity, and development in three chapters. In my first chapter, I develop an original method for quantifying how measurement errors in agricultural survey data affect patterns of productivity observed among smallholder farmers. Applying this method to data from four countries in Sub-Saharan Africa, I show that measurement errors inflate the apparent differences between high- and low-productivity farmers and attenuate how persistent farmers' productivity appears over time. Both these distortions have implications for the evaluation of potential development interventions. In my second chapter, I propose an original econometric framework for measuring the impacts of climate change that correctly incorporates the statistical relationship between climate and weather and distinguishes between impacts resulting from changing weather patterns and those resulting from climate-induced changes in non-weather inputs to production, such as ecosystem services. Applying this framework to data from the U.S., I show that changes in non-weather factors represent a large share of historical climate impacts on agricultural land productivity. My third chapter examines the palm oil processing sector in West Africa. In it, I argue theoretically that, despite producing little oil per unit of fruit processed, small-scale `artisanal' firms can increase the aggregate efficiency of the processing sector when there is significant seasonality in palm fruit yields. I then provide evidence in support of this theory using data from an original survey of oil palm farmers in Ghana. Overall, my dissertation advances new tools for agricultural productivity analysis in the context of climate change, and highlights how climate can shape the organization of agricultural industries.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Maue, Casey Campbell |
|---|---|
| Degree supervisor | Kolstad, Charles D |
| Degree supervisor | Naylor, Rosamond |
| Thesis advisor | Kolstad, Charles D |
| Thesis advisor | Naylor, Rosamond |
| Thesis advisor | Burke, Marshall |
| Thesis advisor | Emerick, Kyle |
| Thesis advisor | Plambeck, Erica L |
| Degree committee member | Burke, Marshall |
| Degree committee member | Emerick, Kyle |
| Degree committee member | Plambeck, Erica L |
| Associated with | Emmett Interdisciplinary Program in Environment and Resources (Stanford University) |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Casey C. Maue. |
|---|---|
| Note | Emmett Interdisciplinary Program in Environment and Resources (Stanford University). |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/tg840gt7368 |
Access conditions
- Copyright
- © 2021 by Casey Campbell Maue
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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