Abstract
Changes in the household economy lie at the heart of the "agricultural transformation". However, the mechanics of this transformation at the micro-level are poorly understood. Investigating this in the neoclassical framework allows us to ask the question: what changes within rural households are needed for this transformation to succeed, and how do men and women manage this transformation? The purpose of this essay is to apply the neoclassical macroeconomic framework of a multisector economy to classical questions of distribution, accumulation, and growth. We propose the the idea of an "industrious revolution" as way to frame many of the concepts discussed in the paper, particularly changes in the rural household economy. Following Hymer and Resnick (1969) we develop a theoretical framework for the industrious revolution. We then searching for answers to a classical questions at the microeconomic or household level, using survey data from rural Bangladesh from 1988 and 2000.
Abstract
We use panel data on rice farmers in the Central Luzon provinces of the Philippines between 1970 and 2016 to test for market completeness, following Benjamin (1992) and LaFave and Thomas (2016). We find that markets in this context are incomplete. This suggests that households rely on labor endowments for their labor demand decisions, rather than solely relying on their production technology to make production decisions. Previously, the recursion test has only been used to identify the existence of market completeness in general; however we show that it can be used to identify one market becoming complete over time. We apply the Benjamin (1992) test to investigate if credit constraints from land reform laws made credit markets incomplete. However, we do not find evidence that credit constraints from land reform laws made credit markets incomplete.
Abstract
Population pressure is speeding the rate of deforestation in Sub-Saharan Africa, raising the monetary and opportunity costs of meal preparation. Many people rely on firewood or charcoal to prepare food. Using a field experiment in Western Zambia, we investigate the impact of solar cook stoves on compositional changes in diet when constraints to cooking nutritionally diverse foods (e.g., legumes) and the cost of meal preparation are removed. We find no impact on diet for those households assigned to the solar stove treatment. We do see a significant result for the average number of dishes per household meal. These results over valuable insights into program development for the provision of solar stoves to reduce the cost of meal preparation.
Abstract
We quantify the significance and magnitude of the effect of measurement error in satellite weather data on modeling agricultural productivity. To provide rigor to our approach, we combine geospatial weather data from a variety of weather products with the geo-referenced household survey data from six Sub-Saharan African countries that are part of the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative. Our goal is to provide systematic evidence on obfuscation methods, satellite data source, and weather metrics in order to determine which of these elements have strong predictive power over a large set of crops and countries and which are only useful in highly specific settings.
Abstract
We provide a review of recent developments in the calculation of standard errors and test statistics for statistical inference. While much of the focus of the last two decades in economics has been on generating unbiased coefficients, recent years has seen a variety of advancements in correcting for non-standard standard errors. We synthesize these recent advances in addressing challenges to conventional inference, like heteroskedasticity, clustering, serial correlation, and testing multiple hypotheses. We also discuss recent advancements in numerical methods, such as the bootstrap, wild bootstrap, and randomization inference. We make three specific recommendations. First, applied economists need to clearly articulate the challenges to statistical inference that are present in data as well as the source of those challenges. Second, modern computing power and statistical software means that applied economists have no excuse for not correctly calculating their standard errors, test statistics, and confidence intervals. Third, because complicated sampling strategies and research designs make it difficult to work out the correct analytical formula for distributions, we believe that in the applied economics profession it should become standard practice to rely on asymptotic refinements to the distribution of estimators, presenting appropriately calculated confidence intervals via bootstrapping. Throughout, we reference built-in and user-written Stata commands that allow one to quickly calculate accurate standard errors and relevant test statistics.