Travis J. Lybbert

Getting Patents and Economic Data to Speak to Each Other: An 'Algorithmic Links with Probabilities' Approach for Joint Analyses of Patenting and Economic Activity

International technological diffusion is a key determinant of cross-country differences in economic performance. While patents can be a useful proxy for innovation and technological change and diffusion, fully exploiting patent data for such economic analyses requires patents to be tied to measures of economic activity. In this paper, we describe and explore a new algorithmic approach to constructing concordances between the International Patent Classification (IPC) system that organizes patents by technical features and industry classification systems that organize economic data, such as the standard International Trade Classification (SITC), the International Standard Industrial Classification (ISIC) and the Harmonized System (HS). This ‘Algorithmic Links with Probabilities’ (ALP) approach incorporates text analysis software and keyword extraction programs and applies them to a comprehensive patent dataset. We compare the results of several ALP concordances to existing technology concordances. Based on these comparisons, we select a preferred ALP approach and discuss advantages of this approach relative to conventional approaches. We conclude with a discussion on some of the possible applications of the concordance and provide a sample analysis that uses our preferred ALP concordance to analyze international patent flows based on trade patterns.

Is Bioprospecting a Viable Strategy for Conserving Tropical Ecosystems

This paper explores whether bioprospecting can reasonably be expected to change rural incentives to conserve tropical ecosystems. Bioprospecting advocates posit that the prospect of discovery ofbiota of immense commercial worth offers an avenue to increase the valuation of nature and endogenously reduce consumptive use of habitat. We consider the microeconomic mechanisms by which bioprospecting might affect incentives and the distributional consequences of these effects.

Booming markets for Moroccan argan oil appear to benefit some rural households while threatening the endemic argan forest

Moroccos argan oil is now the most expensive edible oil in the world. High-value argan markets have sparked a bonanza of argan activity. Nongovernmental organizations, international and domestic development agencies, and argan oil cooperatives aggressively promote the win–win aim of simultaneously benefiting local people and the health of the argan forest. This paper tests some of these win–win claims. Analysis of a panel of detailed household data suggests that the boom has enabled some rural households to increase consumption, increase their goat herds (which bodes poorly for the argan forest), and send their girls to secondary school. The boom has predictably made households vigilant guardians of fruit on the tree, but it has not incited investments in longer term tree and forest health. We evaluate landscape-level impacts of these changes using commune-level data on educational enrollment and normalized difference vegetation index data over the period from 1981 to 2009. The results of the mesoanalysis of enrollment are consistent with the microanalysis: the argan boom seems to have improved educational outcomes, especially for girls. Our normalized difference vegetation index analysis, however, suggests that booming argan prices have not improved the forest and may have even induced degradation. We conclude by exploring the dynamic interactions between argan markets, local institutions, rural household welfare, and forest conservation and sustainability.

RISK‐TAKING BEHAVIOR IN THE PRESENCE OF NONCONVEX ASSET DYNAMICS

The growing literature on poverty traps emphasizes the links between multiple equilibria and risk avoidance. However, multiple equilibria may also foster risk-taking behavior by some poor people. We illustrate this idea with a simple analytical model in which people with different wealth and ability endowments make investment and risky activity choices in the presence of known nonconvex asset dynamics. This model underscores a crucial distinction between familiar static concepts of risk aversion and forward-looking dynamic risk responses to nonconvex asset dynamics. Even when unobservable preferences exhibit decreasing absolute risk aversion, observed behavior may suggest that risk aversion actually increases with wealth near perceived dynamic asset thresholds. Although high ability individuals are not immune from poverty traps, they can leverage their capital endowments more effectively than lower ability types and are therefore less likely to take seemingly excessive risks. In general, linkages between behavioral responses and wealth dynamics often seem to run in both directions. Both theoretical and empirical poverty trap research could benefit from making this two-way linkage more explicit.

Dynamic Field Experiments in Development Economics: Risk Valuation in Morocco, Kenya and Peru

The effective design and implementation of interventions that reduce vulnerability and poverty require a solid understanding of underlying poverty dynamics and associated behavioral responses. Stochastic and dynamic benefit streams can make it difficult for the poor to learn the value of such interventions to them. We explore how dynamic field experiments can help (i) intended beneficiaries to learn and understand these complicated benefit streams, and (ii) researchers to better understand how the poor respond to risk when faced with nonlinear welfare dynamics. We discuss and analyze dynamic risk valuation experiments in Morocco, Peru, and Kenya.

Bayesian Herders: Asymmetric Updating of Rainfall Beliefs in Response to External Forecasts

Temporal climate risk weighs heavily on many of the world’s poor. Model-based climate forecasts could benefit such populations, provided recipients use forecast information to update climate expectations. We test whether pastoralists in southern Ethiopia and northern Kenya update their expectations in response to forecast information and find that they indeed do, albeit with a systematic bias towards optimism. In their systematic optimism, these pastoralists are remarkably like Wall Street’s financial analysts and stockbrokers. If climate forecasts have limited value to these pastoralists, it is due to the flexibility of their livelihood rather than an inability to process forecast information.

Leveling with Friends: Social Networks and Indian Farmers’ Demand for Agricultural Custom Hire Services

This research was undertaken to understand how information about a new agricultural technology is transmitted through social networks, and what effect information gained through social networks has on technology demand at the household level. The technology in question is laser land leveling (LLL)—a resource-conserving technology—which we introduced in eastern Uttar Pradesh, India as part of the study. [IFPRI Discussion Paper No. 01302].

ABC, 123: The Impact of a Mobile Phone Literacy Program on Educational Outcomes

CGD non-resident fellow Jenny Aker and co-authors report on the results from a randomized evaluation of a mobile phone education program (Project ABC) in Niger, in which adult students learned how to use mobile phones as part of a literacy and numeracy class. Overall, students demonstrated substantial improvements in literacy and numeracy test scores. There is also evidence of persistent impacts: six months after the end of the first year of classes, students in the program retained what they had learned better than others. The effects do not appear to be driven by differences in teacher quality or in teacher and student attendance. The results suggest that simple and relatively cheap information and communication technology can serve as an effective and sustainable learning tool for rural populations.

Information Networks Among Women and Men and the Demand for an Agricultural Technology in India

Although there is ample evidence of differences in how and where men and women acquire information, most research on learning household decision-making only considers access to information for a single, typically male, household head. This assumption is problematic in developing-country agriculture, where women play a fundamental role in farming. Using gender-disaggregated social network data from Uttar Pradesh, India, we analyze agricultural information networks among men and women.We test for gender-specific network effects on demand for laser land leveling—a resource-conserving technology—using data from a field experiment that combines a BDM auction with a lottery. We find that factors determining male and female links are similar, although there is little overlap between male and female networks. We also find evidence of female network effects on household technology demand, although male network effects are clearly stronger. Results indicate that extension services can better leverage female networks to promote new technologies.

Targeting Technology to Reduce Poverty and Conserve Resources: Experimental Delivery of Laser Land Leveling to Farmers in Uttar Pradesh, India

Demand heterogeneity often makes it profitable for firms to price and promote goods and services differently in different market segments. When private consumption brings public benefits, this same heterogeneity can be used to target public subsidies. We explore the design of public–private targeting and segmentation strategies in the case of a resource-conserving agricultural technology in India. To understand farmers’ heterogeneous demand for laser land leveling (LLL), we conducted an experimental auction for LLL services with an integrated randomized controlled trial to estimate the private benefits of the technology. We use graphical and econometric approaches to characterize farmer demand for LLL. We then add detailed cost data from LLL providers to simulate and evaluate several potential targeted delivery strategies based on measures of (1) the cost-effectiveness of expanding LLL dissemination, (2) water savings, and (3) market surplus in a welfare framework. These simulations demonstrate inherent tradeoffs between increasing the amount of land that is leveled and expanding the number of farmers who adopt the technology, and between adoption and water savings. While segmenting and targeting are popular elements of many public–private partnerships to develop and disseminate agricultural technologies, formulating and implementing effective delivery strategies requires a rich understanding of costs, benefits, and demand. Our experimental approach generates such an understanding and may be relevant in other contexts.