scholarly journals A Time Series Analysis of China’s Foreign Direct Investment on Senegal’s Agriculture

Author(s):  
Galaye Ndiaye ◽  
Xu He Lian

Since 2000 China has started to strengthen its agricultural co-operation with Africa in trade and other commercial activities. China has increased its agriculture investment in Africa, because of the rapid economic rise of China in many African developing countries. China's investment has developed and opened many opportunities against a backdrop of closer economic ties with many African countries and particularly in Senegal. The purpose of this study was to analyse the times series analysis impact of China's FDI in Senegal's agriculture. The study mainly used secondary data that are collected from the World Bank and IMF for 22 years between 1990 and 2012. The descriptive and econometric model was used to analyse the collected data. Although agricultural growth has increased in Senegal in recent years, food security remains a severe challenge. Despite international and local concerns, China's investment in Senegal in infrastructure and agricultural technology and training could facilitate agricultural growth in Senegal. A time series data is used to get the empirical results for our paper, and the estimation's results show that China's FDI is an important element in Senegal's agriculture will increase employment creation, high productivity, access to the finance and markets for smallholders, technology transfer enforcement of production standards, and farmers can access more to bank credit.

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis


2021 ◽  
Vol 13 (3) ◽  
pp. 1187
Author(s):  
Bokyong Shin ◽  
Mikko Rask

Online deliberation research has recently developed automated indicators to assess the deliberative quality of much user-generated online data. While most previous studies have developed indicators based on content analysis and network analysis, time-series data and associated methods have been studied less thoroughly. This article contributes to the literature by proposing indicators based on a combination of network analysis and time-series analysis, arguing that it will help monitor how online deliberation evolves. Based on Habermasian deliberative criteria, we develop six throughput indicators and demonstrate their applications in the OmaStadi participatory budgeting project in Helsinki, Finland. The study results show that these indicators consist of intuitive figures and visualizations that will facilitate collective intelligence on ongoing processes and ways to solve problems promptly.


2016 ◽  
Vol 50 (1) ◽  
pp. 41-57 ◽  
Author(s):  
Linghe Huang ◽  
Qinghua Zhu ◽  
Jia Tina Du ◽  
Baozhen Lee

Purpose – Wiki is a new form of information production and organization, which has become one of the most important knowledge resources. In recent years, with the increase of users in wikis, “free rider problem” has been serious. In order to motivate editors to contribute more to a wiki system, it is important to fully understand their contribution behavior. The purpose of this paper is to explore the law of dynamic contribution behavior of editors in wikis. Design/methodology/approach – After developing a dynamic model of contribution behavior, the authors employed both the metrological and clustering methods to process the time series data. The experimental data were collected from Baidu Baike, a renowned Chinese wiki system similar to Wikipedia. Findings – There are four categories of editors: “testers,” “dropouts,” “delayers” and “stickers.” Testers, who contribute the least content and stop contributing rapidly after editing a few articles. After editing a large amount of content, dropouts stop contributing completely. Delayers are the editors who do not stop contributing during the observation time, but they may stop contributing in the near future. Stickers, who keep contributing and edit the most content, are the core editors. In addition, there are significant time-of-day and holiday effects on the number of editors’ contributions. Originality/value – By using the method of time series analysis, some new characteristics of editors and editor types were found. Compared with the former studies, this research also had a larger sample. Therefore, the results are more scientific and representative and can help managers to better optimize the wiki systems and formulate incentive strategies for editors.


2013 ◽  
Vol 10 (83) ◽  
pp. 20130048 ◽  
Author(s):  
Ben D. Fulcher ◽  
Max A. Little ◽  
Nick S. Jones

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.


2021 ◽  
Vol 3 (2) ◽  
pp. 69
Author(s):  
Rohim Rohim ◽  
Mike Triani

The purpose of this research is to determine (1) the effect of income on gas consumption in Indonesia (2) the effect of population on gas consumption in Indonesia (3) the effect of industrial growth on gas consumption in Indonesia. This type of research is descriptive and associative. The data used in this research is secondary data from Indonesia in the form of time series data from 1970 to 2019 and this data was obtained from official institutions of the World Bank and BP Statistic World. The data were processed using multiple linear regression. The results showed that the income had a negative and significant effect on gas consumption with a probability value of 0.0005 <0.05, the population had a positive and significant effect on gas consumption with a value of prob t-count of 0.0010 <0.05 and industrial growth had a positive and significant effect on gas consumption.  The significant to gas consumption in Indonesia with a value of prob t-count value of 0.5219 <0.05 and suggestions for further researchers to be able to analyze other factors that affecting gas consumption in Indonesia.  Because from the gas sectors, there are still many factors that affected gas consumption until the research results will be better


2018 ◽  
Vol 3 (4) ◽  
pp. 525-533
Author(s):  
Raudhatul Husna ◽  
Azhar Azhar ◽  
Edy Marsudi

Abstrak. Alih fungsi lahan atau lazimnya disebut sebagai konversi lahan adalah  perubahan fungsi sebagian atau seluruh kawasan lahan dari fungsinya semula (seperti yang direncanakan) menjadi fungsi lain yang membawa dampak negatif terhadap lingkungan dan potensi lahan itu sendiri. Penelitian ini bertujuan untuk mengetahui apakah harga lahan, kepadatan penduduk, produktivitas padi dan jumlah PDRB dapat mempengaruhi alih fungsi lahan sawah di Kabupaten Aceh Besar. Data yang digunakan dalam penelitian ini adalah data sekunder. Data yang dikumpulkan adalah data time series dengan range tahun 2002 sampai 2016. Penelitian ini menggunakan metode analisis  regresi linier berganda. hasil penelitian dan pembahasan serta pengujian SPSS menunjukkan bahwa harga lahan, kepadatan penduduk, dan produktivitas padi berpengaruh nyata terhadap alih fungsi lahan sawah di Kabupaten Aceh Besar. sedangkan jumlah PDRB tidak berpengaruh terhadap alih fungsi lahan sawah. Hal ini ditunjukkan oleh koefisien regresi untuk variabel jumlah PDRB sebesar 0,00015. Hasil pengujian statistik menunjukkan nilai t hitung untuk jumlah PDRB sebesar 1,315 dengan nilai signifikan sebesar 0,218. Sedangkan nilai t tabel sebesar 1,782 yang berarti nilai t hitung t tabel (1,315 1,782).  Factors Affecting The Conversion Of Paddy Fields In Kabupaten Aceh Besar Abstract. Land use change or commonly referred to as land conversion is a change in the function of part or all of the land area from its original function (as planned) into other functions that bring negative impacts to the environment and the potential of the land itself. This study aims to find out whether the price of land, population density, rice productivity and the amount of GRDP can affect the conversion of rice field functions in Aceh Besar District. The data used in this research is secondary data. The data collected is time series data with range of year 2002 until 2016. This research use multiple linier regression analysis method. the results of research and discussion and testing of SPSS showed that land price, population density, and rice productivity significantly affected the conversion of wetland in Aceh Besar district. while the number of GDP does not affect the conversion of wetland. This is indicated by the regression coefficient for the GRDP variable of 0.00015. The results of statistical tests show the value of t arithmetic for the amount of GRDP by 1.315 with a significant value of 0.218. While the value of t table of 1.782 which means the value of t arithmetic t table (1,315 1.782).


Media Ekonomi ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 83
Author(s):  
Jumadin Lapopo

<p>Poverty is being a problem in all developing countries including Indonesia. Among goverment programs, poverty has become the center offattention in policy at both of the regional and national levels. Looking at thephenomenon of poverty, Islam present with solution to reduce poverty through Zakat. This study aims to analyze the effect of ZIS and Zakat Fitrah against poverty in Indonesia in 1998 until 2010, data used in this study is secondary data and uses time series data, for the dependent variabel is poverty and for independent variables are ZIS and Zakat Fitrah. The analysis tools used in this study is to use multiple regression analysis model and the assumptions of classical test using the software Eviews-4. In this study also concluded that the ZIS variables significantly affect to the reduction of poverty in Indonesia although the effect is very small. In the variable Zakat Fitrah not significantly affect poverty reduction in Indonesia because of the nature of Zakat Fitrah is for consumption and not for long-term needs. The results of this study can be used for the management of zakat to be able to develop the management and to get a better system for distribution of zakat so that the main purpose of zakat can be achieved to reduce poverty.<br />Keywords : Poverty, Zakat Fitrah, ZIS.</p>


2019 ◽  
Vol 16 (1) ◽  
pp. 1-10
Author(s):  
Novegya Ratih Primandari

This research aims to analyze effect of economic growth, inflation and Unemployment on the Rate of Poverty in the Province of South Sumatera. This research used secondary data in the form of time series data from 2001-2017. The method used quantitative approach by applying a linear regression model with OLS estimation Ordinary Least Square (OLS) method. The results of this study indicate that partially and simultaneously Economic Growth, Inflation and Unemployment have a significant effect on the Poverty Rate in the Province of South Sumatera.


1986 ◽  
Vol 2 (3) ◽  
pp. 331-349 ◽  
Author(s):  
John J. Beggs

This article proposes the use of spectral methods to pool cross-sectional replications (N) of time series data (T) for time series analysis. Spectral representations readily suggest a weighting scheme to pool the data. The asymptotically desirable properties of the resulting estimators seem to translate satisfactorily into samples as small as T = 25 with N = 5. Simulation results, Monte Carlo results, and an empirical example help confirm this finding. The article concludes that there are many empirical situations where spectral methods canbe used where they were previously eschewed.


Author(s):  
Pēteris Grabusts ◽  
Arkady Borisov

Clustering Methodology for Time Series MiningA time series is a sequence of real data, representing the measurements of a real variable at time intervals. Time series analysis is a sufficiently well-known task; however, in recent years research has been carried out with the purpose to try to use clustering for the intentions of time series analysis. The main motivation for representing a time series in the form of clusters is to better represent the main characteristics of the data. The central goal of the present research paper was to investigate clustering methodology for time series data mining, to explore the facilities of time series similarity measures and to use them in the analysis of time series clustering results. More complicated similarity measures include Longest Common Subsequence method (LCSS). In this paper, two tasks have been completed. The first task was to define time series similarity measures. It has been established that LCSS method gives better results in the detection of time series similarity than the Euclidean distance. The second task was to explore the facilities of the classical k-means clustering algorithm in time series clustering. As a result of the experiment a conclusion has been drawn that the results of time series clustering with the help of k-means algorithm correspond to the results obtained with LCSS method, thus the clustering results of the specific time series are adequate.


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