Michael S. Delgado

The Transition to Modern Agriculture: Contract Farming in Developing Economies

Recent years have seen considerable interest in the impact of contract farming on farmers in developing countries, motivated out of belief that contract farming spurs transition to modern agriculture. In this article, we provide a thorough review of the empirical literature on contract farming in both developed and developing countries, using China as a special case of the latter. We pay careful attention to broad implications of this research for economic development. We first find empirical studies consistently support the positive contribution of contract farming to production and supply chain efficiency. We also find that most empirical studies identify a positive and significant effect of contract farming on farmer welfare, yet are often unable to reach consistent conclusions as to significant correlates of contract participation.

Does Education Matter for Economic Growth

Empirical growth regressions typically include mean years of schooling as a proxy for human capital. However, empirical research often finds that the sign and significance of schooling depends on the sample of observations or the specification of the model. We use a nonparametric local-linear regression estimator and a nonparametric variable relevance test to conduct a rigorous and systematic search for significance of mean years of schooling by examining five of the most comprehensive schooling databases. Contrary to a few recent papers that have identified significant nonlinearities between education and growth, our results suggest that mean years of schooling is not a statistically relevant variable in growth regressions. However, we do find evidence (within a cross-sectional framework), that educational achievement, measured by mean test scores, may provide a more reliable measure of human capital than mean years of schooling.

Fixed vs Random: The Hausman Test Four Decades Later

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

Dynamic adjustment in agricultural practices to economic incentives aiming to decrease fertilizer application

Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term.

Quantifying the Effects of Underground Natural Gas Storage on Nearby Residents

We estimate the potential negative effects of underground natural gas storage on local residents using hedonic regression and a sample of Indiana properties transacted between 2004 and 2013. We find that underground natural gas storage activities significantly reduce property values. Property values increase by about 10 percent at a distance of 1 kilometer from a storage field. Each additional storage well and observation well located near a property reduces the propertys value by about 0.43 percent and 2.64 percent, respectively. Our research sheds new light on a previously unexplored aspect of natural gas resource activities.

Another round of fraternity membership and binge drinking

This paper describes a successful attempt to replicate DeSimone [5] which investigates the effect of fraternity membership on binge drinking using both probit and interval regression models. We encountered software-related difficulties that hampered our repl ication effort, though ultimately we showed that DeSimone’s published results are replicable. This is due to default settings in Stata that correctly identify the problem of complete separation, in which the maximum likelihood estimator does not exist. Other statistical packages, such as R, do not recognize the complete separation problem and do not automatically remove the observations before estimation. This poses several econometric obstacles for replication. Without prior knowledge of which observations Stata drops from the probit regression, inconsistencies between the samples used for the probit and interval regression models would arise, regardless of which software package is used. Second, when attempting replication in a program, such as the GLM function in R, that does not automatically remove the necessary observations, one will not be able to exactly duplicate the results due to a sample that is not identical to the one use d for estimation by Stata. Thus, without knowledge of which observations are dropped, precise replication would be impossible. Therefore, we advocate the benefits of data/code archives in facilitating accurate verification of published results. We find that once the correct sample is obtained we are able to ide ntically replicate the paper. It should be noted that the results are qualitatively identical, regard less of which sample size or software package is used.

Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions

Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are derived from complex modeling techniques that may include model simulation and other data processing. We develop a transparent econometric framework that uses pixel level biophysical measurements and aggregate cropland statistics to develop pixel level cropland allocation predictions. Such pixel level land use data can be used to investigate the impact of human activities on the environment. Validation exercises show that our approach is effective at downscaling cropland allocation to multiple levels of resolution.

Foreign Direct Investment and Growth Symbiosis: A Semiparametric System of Simultaneous Equations Analysis

Abstract We characterize the types of interactions between foreign direct investment (FDI) and economic growth, and analyze the effect of institutional quality on such interactions. To do this analysis, we develop a class of instrument-based semiparametric system of simultaneous equations estimators for panel data and prove that our estimators are consistent and asymptotically normal. Our new methodological tool suggests that across developed and developing economies, causal, heterogeneous symbiosis and commensalism are the most dominant types of interactions between FDI and economic growth. Higher institutional quality facilitates, impedes or has no effect on the interactions between FDI and economic growth.

The Special Issue on Chinese Food, Agricultural and Rural Economics

At the new release of the 2016 Number One Document of the Chinese Central Government, public attention is drawn to food, agricultural, and rural issues facing China. The 1.4 billion population of China is supported to a large extent by food produced domestically; however, its small percentage of food supply comes from imports, which means a large volume of agricultural commodities, and this has an important implication to the world. Important issues that concern the public, government, and researchers include food quality and safety, food security pressured by the availability and quality of water and land, and rural human resources in terms of both quantity and quality of farm labor. In this special issue, we have five articles addressing different aspects of these issues. The articles in this special issue were presented at the 2015 Chinese Economist Society Annual Conference held in Chongqing. We received submissions from scholars in China, the United States, Canada, and the European Union, and accepted five articles. Chinese consumers have experienced steady income growth and thus have gained an appetite and purchasing power for more expensive and higher quality food, such as animal protein items. Furthermore, food safety problems stemming from the Chinese domestic food supply chain

Finite sample performance of specification tests for correlated random effects quantile panel regressions

ABSTRACT We investigate the finite sample performance of the Abrevaya and Dahl (2008) test for coefficient heterogeneity for a correlated random effects ‘mean’ (CREM) panel quantile regression estimator. We assess size and power of the test over a range of sample sizes and panel dimensions. The test is undersized for small-to-moderate sample sizes and displays low power even with a high degree of heteroscedasticity. Size and power improve substantially in larger samples. Our results provide insight for applied researchers.