Topics in Economic Development

Paper Session

Sunday, Jan. 8, 2017 1:00 PM – 3:00 PM

Hyatt Regency Chicago, Grand Suite 5
Hosted By: American Economic Association
  • Chair: Christian Ahlin, Michigan State University

Newer Need Not Be Better: Evaluating the Penn World Tables and the World Development Indicators Using Nighttime Lights

Maxim Pinkovskiy
,
Federal Reserve Bank of New York
Xavier Sala-i-Martin
,
Columbia University and NBER

Abstract

Nighttime lights data are a measure of economic activity whose error is plausibly independent of the measurement errors of most conventional indicators. Therefore, we can use nighttime lights as an independent benchmark to assess existing measures of economic activity (Pinkovskiy and Sala-i-Martin (2016)). We employ this insight to find out which vintages of the Penn World Tables and of the World Development Indicators better estimate true income per capita. We find that revisions of the PWT do not necessarily dominate their predecessors in terms of explaining nighttime lights (and thus, predicting unobserved true income). In particular, we find that the PWT 7.1 chain-based GDP series substantially outperforms the constant-price series in PWT 9.0, the most recent vintage of the PWT. We additionally find that the World Development Indicators are as good, and often better, measures of unobserved true income as are recent vintages of the Penn World Tables. Furthermore, we find that each new round of the International Comparisons Programme (ICP) has improved the WDI's ability to predict log unobserved true income. We also find that vintages tend to be good or bad at predicting unobserved true income roughly equally across the sample period, and do not tend to be particularly good at predicting unobserved income in the year of their price survey. We conclude that GDP series based on unadjusted domestic growth rates alone predict growth rates of true income better than series based on PPP adjustments to growth rates.

Liquid Milk: Cash Constraints and Intertemporal Choice among Dairy Farmers in Western Kenya

Berber Kramer
,
International Food Policy Research Institute
Xin Geng
,
International Food Policy Research Institute
Wendy Janssens
,
Tinbergen Institute and VU University Amsterdam

Abstract

This paper tests whether cash constraints affect preferences over the timing of income, using high-frequency panel data of intertemporal choice among Kenyan dairy farmers. When selling milk, these farmers choose between a cooperative, which defers payments by approximately one month, and the market, which pays upon delivery. As such, intra-household variation in the choice where to sell milk will reflect variation in the marginal rate of substitution and cash needs should hence induce farmers to sell relatively more milk in the market. Semi-parametric panel data estimates yield robust evidence of this theory. Although the market pays on average less than the cooperative, a substantial number of farmers sell in the market, especially in weeks with less cash at hand, and in weeks with increased cash needs due to uninsured health
shocks. Financial instruments that can help relax cash constraints may encourage farmers in need of cash to keep selling to the cooperative, which potentially improves farmers’ loyalty to welfare-enhancing collective marketing arrangements.

We Don't Need No Education: Reconstruction and Conflict Across Afghanistan

Travers Barclay Child
,
VU University Amsterdam and Tinbergen Institute

Abstract

Field interviews conducted by the author in Afghanistan suggest current theories linking conflict to development do not adequately account for ideological drivers of resistance. We present a simplified model demonstrating how reconstruction activities of an occupier can exacerbate violence through popular discontent if projects are ideologically controversial. We test the model using detailed military reconstruction data from NATO, and a US Government assembled violence log covering Afghanistan from 2005 until 2009. We find projects in the education sector lead to an uptake in violence, whereas health programming reduces violence. The destabilizing effects of education projects are strongest in conservative areas. Our findings do not appear driven by reverse causation, and are robust when considering many sources of endogeneity. Moreover, the data do not support other existing theories linking conflict to development.

Tropical oil crops and rural poverty

Ryan B. Edwards
,
Stanford University

Abstract

The tripling of area planted with tropical oil crops since the 1990s represents the most significant global agricultural transformation since the green revolution. I study the poverty impacts of the largest modern plantation-based agricultural expansion, Indonesian palm oil over the 2000s. Causal effects are identified by instrumenting the decadal expansion in the area planted with oil palm in each district with its agro-climatically attainable yield. Of the more than 10 million Indonesians lifted from poverty over the 2000s, my most conservative estimate suggests at least 1.3 million rural people have escaped poverty due to growth in the palm oil sector. The areal expansion increased expenditure for low income households and expanded rural public services related to agricultural manufacturing, specifically road networks and households’ access to electricity.

Weather Variability, Technical Change, and Agricultural Production: 40 Years of Evidence From India

Jeffrey D. Michler
,
University of Illinois-Urbana-Champaign
Gerald E. Shively
,
Purdue University
Patrick S. Ward
,
International Food Policy Research Institute

Abstract

Weather variability plays a key role in determining yields in agricultural production. However, new technologies, in the form of fertilizers, pesticides, and drought or flood tolerant seeds, help insulate farmers against the realization of uncertain weather events. This paper poses the question: how large of a role does the weather play in determining variability of agricultural production in India and to what extent has technical change mitigated farmer exposure to bad weather? I develop an innovative application of multilevel modeling and Bayesian estimation to long run production data. This allows me to explicitly model the covariance structure in the data and identify the impact of both weather and technological change on the variance of crop output. Thus, I able to not only estimate the role weather plays in agricultural production but show that the Green Revolution has both increased mean yields while reducing yield variability over the last 40 years. To conduct my empirical analysis I use household level data from six villages in the Village Dynamics Study of South Asia. The data set includes parcel level input and output information for the period 1975-2015. This provides me with 14,657 observations from 10,598 parcels for 766 households. I use satellite weather data and information from ICRISAT on the timing of new technology introduction to the six villages to generate estimates on the impacts of weather and technology on crop output. My results fill a major research gap by estimating the role weather plays in the variability of agricultural production. In identifying weather variability I, of necessity, also identify technological change. I am then able to provide quantitative evidence of the impact of the Green Revolution on both the mean and variance of crop production and show that these new technologies have indeed help insulate farmers from potentially damaging weather events.
JEL Classifications
  • O1 - Economic Development