Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018

IF 4.4 2区 经济学 Q1 AGRICULTURAL ECONOMICS & POLICY
J. G. Ribeiro, S. M. Piedade
{"title":"Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018","authors":"J. G. Ribeiro, S. M. Piedade","doi":"10.1108/caer-01-2022-0014","DOIUrl":null,"url":null,"abstract":"PurposeThe state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool for time series, through applications of splines interpolations, in 46 of its municipalities that had missing data in the variables soybean production in thousand tons, production value and soy derivatives in R$ thousand, and also to assess the differences between the observed series and those with imputed values, in each of these municipalities, in these variables.Design/methodology/approachThe proposed methodology was based on the use of the univariate imputation method through the application of cubic spline interpolation in each of the 46 municipalities, for each of the 3 variables. Then, for each municipality, the original series were compared with each observed series plus the values imputed in these variables by the Quenouille test of correlation of time series.FindingsIt was observed that, after imputation, all series were compared with those observed and are equal by the Queinouille test in the 46 municipalities analyzed, and the Wilcoxon test also showed equality for the accumulated total of the three variables involved with the production of soybeans. And there were increases of 5.92%, 3.58% and 2.84% for soy production, soy production value and soy derivatives value accumulated in the state after imputation in the 46 municipalities.Originality/valueThe present research and its results facilitate the process of estimates and monitoring the total soy production in the state of Mato Grosso and its municipalities from 1990 to 2018.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Agricultural Economic Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1108/caer-01-2022-0014","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 1

Abstract

PurposeThe state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool for time series, through applications of splines interpolations, in 46 of its municipalities that had missing data in the variables soybean production in thousand tons, production value and soy derivatives in R$ thousand, and also to assess the differences between the observed series and those with imputed values, in each of these municipalities, in these variables.Design/methodology/approachThe proposed methodology was based on the use of the univariate imputation method through the application of cubic spline interpolation in each of the 46 municipalities, for each of the 3 variables. Then, for each municipality, the original series were compared with each observed series plus the values imputed in these variables by the Quenouille test of correlation of time series.FindingsIt was observed that, after imputation, all series were compared with those observed and are equal by the Queinouille test in the 46 municipalities analyzed, and the Wilcoxon test also showed equality for the accumulated total of the three variables involved with the production of soybeans. And there were increases of 5.92%, 3.58% and 2.84% for soy production, soy production value and soy derivatives value accumulated in the state after imputation in the 46 municipalities.Originality/valueThe present research and its results facilitate the process of estimates and monitoring the total soy production in the state of Mato Grosso and its municipalities from 1990 to 2018.
1990年至2018年巴西马托格罗索州大豆产量的缺失数据估计
目的马托格罗索州是巴西最大的大豆生产国和出口国;鉴于这一重要性,其目的是建议通过样条插值的应用,在其46个城市中使用时间序列的单变量插补工具,这些城市在变量大豆产量(千吨)、产值和大豆衍生物(千雷亚尔)中存在缺失数据,并评估观察到的序列与具有插补值的序列之间的差异,在每个城市,在这些变量中。设计/方法/方法所提出的方法基于单变量插补方法,通过在46个市镇中的每个市镇应用三次样条插值,对3个变量中的每个变量进行插补。然后,对于每个市政当局,将原始序列与每个观察到的序列加上通过时间序列相关性的Quenouille检验估算在这些变量中的值进行比较。发现据观察,在插补后,所有系列都与所观察到的系列进行了比较,并且在所分析的46个市镇中,通过Queinouille检验,这些系列是相等的,Wilcoxon检验也显示了与大豆生产有关的三个变量的累计总数是相等的。46个市镇的大豆产量、大豆生产价值和大豆衍生物价值在国家累计插补后分别增长了5.92%、3.58%和2.84%。原创性/价值本研究及其结果有助于评估和监测1990年至2018年马托格罗索州及其市镇的大豆总产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
China Agricultural Economic Review
China Agricultural Economic Review AGRICULTURAL ECONOMICS & POLICY-
CiteScore
9.80
自引率
5.90%
发文量
41
审稿时长
>12 weeks
期刊介绍: Published in association with China Agricultural University and the Chinese Association for Agricultural Economics, China Agricultural Economic Review publishes academic writings by international scholars, and particularly encourages empirical work that can be replicated and extended by others; and research articles that employ econometric and statistical hypothesis testing, optimization and simulation models. The journal aims to publish research which can be applied to China’s agricultural and rural policy-making process, the development of the agricultural economics discipline and to developing countries hoping to learn from China’s agricultural and rural development.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信