Estimating Sequential Multi-Choice Demand : An Application to Pesticides Utilization in France.

Crop Production/Industries, Demand and Price Analysis,

Pesticides Uses in Crop Production: What Can We Learn from French Farmers Practices?

This article focuses on the demand system of French farmers concerning pesticides uses. We estimate the demand elasticities of herbicides, insecticides and fungicides with respect to pesticide expenditure, and considering crop differentiation. Then we compare two indexes that are used in agronomic literature to measure the intensity of pesticides uses. We retain a Linear Approximated Almost Ideal Demand System (LA/AIDS) specification. A Full-Information Maximum Likelihood estimation procedure is used for dealing with the problem of censored dependent variable. We consider two cross-sections observed in 2001 and 2006 covering pesticides uses of three crops. We confirm the previous results of the literature that farmers response to price variation is very low, with higher prices response in 2006 than in 2001. Moreover, we find that conditional herbicides expenditure elasticities are often higher than insecticides expenditure elasticities, but lower than those of fungicides. We find higher own-price elasticities for herbicides and fungicides than for insecticides, which is the less used. Finally, application dose seems statistically better to explain herbicides decision, whereas treatment frequency index appears better for insecticides and fungicides. However, most of elasticities are closed for dose and treatment frequency index.Pesticides, LA/AIDS, Elasticities, Censored System of Equations, Two-Step procedure, Quasi Maximum Likelihood, Full-Information Maximum Likelihood., Agricultural and Food Policy, Crop Production/Industries, Demand and Price Analysis, C30, C31, C34, L11, Q11, Q12,

Forecasting with Spatial Panel Data

This paper compares various forecasts using panel data with spatial error correlation. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial correlation, or ignoring heterogeneity due to the individual effects, using Monte Carlo experiments. In addition, we check the performance of these forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models.forecasting, BLUP, panel data, spatial dependence, heterogeneity

Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption

This paper contrasts the performance of heterogeneous and shrinkage estimators versus the more traditional homogeneous panel data estimators. The analysis utilizes a panel data set from 21 French regions over the period 1973-1998 and a dynamic demand specification to study the gasoline demand in France. Out-of-sample forecast performance as well as the plausibility of the various estimators are contrasted.Panel data; French gasoline demand; Error components; Heterogeneous estimators; Shrinkage estimators

Climate variation and corn price volatility : a partial equilibrium model

Dr. Wyatt Thompson, Thesis Supervisor.|Field of study: Agricultural and applied economics."December 2017."Projected future climate changes in the US Corn Belt provides motivation to study how these changes will affect the volatility of crop prices. Recent publications focused on how these changes in climate and climate variability affect the volatility of crop prices and yields, but we are aware of no research that focuses on how the changing of climate variability alone will affect the volatility of yields and area, as well as the market consequences. Considering these indicators, past publications do not account for the timing and intensity of weather variables when estimating the price impacts of climate driven changes to yields and area. This study builds on the previous literature to estimate how the timing of specific weather variables, important to corn yields and area, will affect the volatility of corn prices. The study finds that, under future climate scenarios, corn price volatility could increase, causing a potential change in producer receipts and a potential increase in government costs.Includes bibliographical references (pages 54-57)

Panel Data Inference under Spatial Dependence

This paper focuses on inference based on the usual panel data estimators of a one-way error component regression model when the true specification is a spatial error component model. Among the estimators considered, are pooled OLS, random and fixed effects, maximum likelihood under normality, etc. The spatial effects capture the cross-section dependence, and the usual panel data estimators ignore this dependence. Two popular forms of spatial autocorrelation are considered, namely, spatial auto-regressive random effects (SAR-RE) and spatial moving average random effects (SMA-RE). We show that when the spatial coefficients are large, test of hypothesis based on the usual panel data estimators that ignore spatial dependence can lead to misleading inference

Seemingly Unrelated Regressions with Spatial Error Components

This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with spatial error correlation. The true data generating process is assumed to be SUR with spatial error of the autoregressive or moving average type. Moreover, the remainder term of the spatial process is assumed to follow an error component structure. Both maximum likelihood and generalized moments (GM) methods of estimation are used. Using Monte Carlo experiments, we check the performance of these estimators and their forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous versus homogeneous panel data models

A time-space dynamic panel data model with spatial moving average errors

This paper focuses on the estimation and predictive performance of several estimators for the time-space dynamic panel data model with Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. A dynamic spatial Generalized Moments (GM) estimator is proposed which combines the approaches proposed by Baltagi, Fingleton and Pirotte (2014) and Fingleton (2008). The main idea is to mix non-spatial and spatial instruments to obtain consistent estimates of the parameters. Then, a forecasting approach is proposed and a linear predictor is derived. Using Monte Carlo simulations, we compare the short-run and long-run e¤ects and evaluate the predictive effficiencies of optimal and various suboptimal predictors using the Root Mean Square Error (RMSE) criterion. Last, our approach is illustrated by an application in geographical economics which studies the employment levels across 255 NUTS regions of the EU over the period 2001-2012, with the last two years reserved for prediction

Impact of JayDoc Free Clinic on Emergency Department Usage in Kansas City

Introduction.JayDoc Free Clinic (JayDoc) serves medical needs of uninsured patients in the Kansas City metropolitan area. It is known that patients who have access to primary care are less likely to visit their local Emergency Department (ED) for non-emergent needs. However, it is not well described if JayDoc lowers usage of The University of Kansas Health System (TUKHS) ED. This is the first study to assess the patient referral process between TUKHS ED and JayDoc. Methods. The authors administered a voluntary survey to every patient triaged at JayDoc, even if they were ultimately not accepted for a visit. Items on the questionnaire included health insurance status, primary language, and access to a primary care physician. The authors included questions on the usage of TUKHS ED in the last 12 months.  Results.Seventy-three patients completed the questionnaire. Approximately 10% of respondents reported they visited the ED in the last 12 months and received a referral to JayDoc from staff. However, authors observed no statistically significant difference in the proportion of new patients who used the ED in the last 12 months compared to that of returning patients. Conclusions.Results of this study demonstrated an existing referral system between JayDoc and TUKHS ED. However, the authors could not conclude that JayDoc reduces non-emergent ED visits among its patient population. Future initiatives will include further education to ED providers to increase the number of patients being referred to JayDoc