Estimation of World Food Production with Panel Data Lee, M.H., Korea University at Sejong, Sejong, Republic of Korea; Lee, J.H., IBK Economic Research Institute, Seoul, Republic of Korea; Lee, C.L., Korea University at Sejong, Sejong, Republic of Korea
The Journal of the Korean Society of International Agriculture,
(Dec 2012), Volume:
24, Issue:
5
Journal Article
Peer reviewed
We estimate the global-level food production function with panel data of 148 countries for 1970~2000. In as much as food crisis is mainly caused by the supply shock and likely to happen on a global ...or regional scale beyond territories, estimation of global or regional food production function warrants utmost importance in international cooperation to prevent food crises. In this paper we estimate a Cobb-Douglas food production function by applying a fixed-effect model and test whether the coefficient of each explanatory variable is homogeneous among the five regions encompassing the 148 countries. Our findings are as follows: First, except for temperature, all explanatory variables prove to be significantly important to account for the changes in the world's food production. Second, the coefficient for each explanatory variable is different from region to region. Especially, the coefficients for temperature and precipitation appear quite different across regions. It may reflect the fact that some regions are in a more developed stage in agricultural technology and infrastructure than in other regions.
We consider estimation and test problems for some semiparametric two-sample density ratio models. The profile empirical likelihood (EL) poses an irregularity problem under the null hypothesis that ...the laws of the two samples are equal. We show that a dual form of the profile EL is well defined even under the null hypothesis. A statistical test, based on the dual form of the EL ratio statistic (ELRS), is then proposed. We give an interpretation for the dual form of the ELRS through
φ
-divergences and duality techniques. The asymptotic properties of the test statistic are presented both under the null and the alternative hypotheses, and approximation of the power function of the test is deduced.
The research subject is the computational complexity of the probabilistic neural network (PNN) in the pattern recognition problem for large model databases. We examined the following methods of ...increasing the efficiency of a neural-network classifier: a parallel multithread realization, reducing the PNN to a criterion with testing of homogeneity of feature histograms of input and reference images, approximate nearest-neighbor analyses (Best-Bin First, directed enumeration methods). The approach was tested in facial-recognition experiments with FERET dataset.
The problem of testing homogeneity in contingency tables when the data are spatially correlated is considered. We derive statistics defined as divergences between unrestricted and restricted ...estimated joint cell probabilities and we show that they are asymptotically distributed as linear combinations of chi-square random variables under the null hypothesis of homogeneity. Monte Carlo simulation experiments are carried out to investigate the behavior of the new divergence test statistics and to make comparisons with the statistics that do not take into account the spatial correlation. We show that some of the introduced divergence test statistics have a significantly better behavior than the classical chi-square test for the problem under consideration when we compare them on the basis of the simulated sizes and powers.
The purpose of the paper was to introduce the test for homoscedasticity and the SAS implementation. The test of homogeneity of variance could be divided into the following three categories, ①analysis ...of variance directly based on comparison of variances, ②analysis of variance based on mean comparison was adopted for the new data from the variable transformation of the original data, ③the method of the χ2 test was used to analyze the quantitative raw data which followed the normal distribution. In the first category, a test statistic that followed the F distribution was constructed directly based on the variance ratio of the two samples. In the second category, there were a variety of different variable transformation approaches for the original data, and the new data after the transformation, which was viewed as the univariate quantitative data collected from a single-factor with multi-level design, was analyzed by using one-way ANOVA. In the third category, the χ2 test statistic was constructed for quantitat
This article develops influence diagnostics for log‐Birnbaum–Saunders (LBS) regression models with censored data based on case‐deletion model (CDM). The one‐step approximations of the estimates in ...CDM are given and case‐deletion measures are obtained. Meanwhile, it is shown that CDM is equivalent to mean shift outlier model (MSOM) in LBS regression models and an outlier test is presented based on MSOM. Furthermore, we discuss a score test for homogeneity of shape parameter in LBS regression models. Two numerical examples are given to illustrate our methodology and the properties of score test statistic are investigated through Monte Carlo simulations under different censoring percentages.
This study focuses on changes in irradiance, temperature, precipitation, evaporation, snow cover, and water balance in Saxony (eastern Germany) over the past 50 yr. It had 2 main objectives: (1) ...collection of all available climatological data with daily resolution, (2) statistical analysis of the climate. Time series of more than 600 meteorological stations from Saxony and the surrounding regions have been organized in the Saxon climate databank. This databank contains tools for homogeneity tests and trend analysis of climatologic time series. This makes it possible to calculate derived and complex quantities from single climate elements. About half of the time series tested were sufficiently homogeneous for a regional climate analysis of Saxony. The most important results of the trend analysis are: (1) marked decrease in summer rainfall (−10 to −30%); (2) significant increase in winter precipitation; (3) increase in heavy rainfall events during early summer; (4) increase in the length and frequency of dry periods in both vegetation periods; (5) increase in temperature in all seasons, and especially in winter (>2°C in northern Saxony); (6) increase in irradiance and potential evaporation by about 7% in the last 30 years.
간헐적인 패널 시계열 자료의 개념과 구조를 소개하고, 간헐적인 패널 시계열 자료의 모형으로 간헐적인 패널 1차 자기회귀 모형을 고려하였다. 간헐적인 패널 1차 자기회귀 모형의 동질성 검정을 위하여 Wald 검정통계량을 제안하고, 그 극한분포를 제시하였다. 또한 동질성이 만족되는 경우 시점 별 평균을 이용하여 종합한 자료로 모형을 적합하였다. 이 모형의 ...동질성 검정 통계량의 극한분포가 $\chi^{2}$분포에 잘 따르는지를 알아보기 위해 모의실험을 실시하고, 실제 자료 분석으로 지역별 월별 Mumps 자료에 간헐적인 패널 1차 자기회귀 모형을 적합하여 동질성 검정을 수행한 결과 동질성을 만족하였다. 동질성이 만족된 지역별 월별 Mumps 자료를 시점 별 평균을 이용하여 종합하고 1 차 자기회귀 모형으로 적합하였다.
The concepts and structure of intermittent panel time series data are introduced. We suggest a Wald test statistic for the test of homogeneity for intermittent panel first order autoregressive model and its limit distribution is derived. We consider the fitting the model with pooling data using sample mean at the time point if homogeneity for intermittent panel AR(1) is satisfied. We performed simulations to examine the limit distribution of the homogeneity test statistic for intermittent panel AR(1). In application, we fit the intermittent panel AR(1) for panel Mumps data and investigate the test of homogeneity.
A fundamental question in response-adaptive randomization is: What allocation proportion should we target to achieve required power while resulting in fewer treatment failures? For comparing two ...treatments, such optimal allocations are well studied in the literature. However, few authors address the question for multiple treatments and the generalization of optimal allocations is necessary in practice. We are interested in finding the optimal allocation proportion, which achieves a required power of a multivariate test of homogeneity in binary response experiments while minimizing expected treatment failures at the same time. We propose such an optimal allocation for three treatments by giving an analytical solution for the optimization problem. Numerical studies show that a response-adaptive randomization procedure that targets proposed optimal allocation is superior to complete randomization. We also discuss some future research topics and additional issues on optimal adaptive designs.
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