Producers' Response to Changes in Prices and Marketing Policies: A Case Study of Sugarcane and Paddy in Eastern U.P. by S. C. Gupta and A. Majid. New York: Asia Publishing House, 1965.

1968 ◽  
Vol 8 (2) ◽  
pp. 308-309
Author(s):  
Mohammad Irshad Khan
Keyword(s):  
New York ◽  
Time Series ◽  
Time Series Data ◽  
Publishing House ◽  
Economic Incentives ◽  
The Other ◽  
Series Data ◽  
Poor Countries ◽  
Northern India

It is alleged that the agricultural output in poor countries responds very little to movements in prices and costs because of subsistence-oriented produc¬tion and self-produced inputs. The work of Gupta and Majid is concerned with the empirical verification of the responsiveness of farmers to prices and marketing policies in a backward region. The authors' analysis of the respon¬siveness of farmers to economic incentives is based on two sets of data (concern¬ing sugarcane, cash crop, and paddy, subsistence crop) collected from the district of Deoria in Eastern U.P. (Utter Pradesh) a chronically foodgrain deficit region in northern India. In one set, they have aggregate time-series data at district level and, in the other, they have obtained data from a survey of five villages selected from 170 villages around Padrauna town in Deoria.

A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data

2021 ◽  
Vol 24 ◽  
pp. 100618
Author(s):  
Philipe Riskalla Leal ◽  
Ricardo José de Paula Souza e Guimarães ◽  
Fábio Dall Cortivo ◽  
Rayana Santos Araújo Palharini ◽  
Milton Kampel
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Time Series Data ◽  
Remotely Sensed ◽  
Series Data ◽  
Precipitation Time Series ◽  
New Approach

CAUSAL RELATIONSHIP OF ENERGY CONSUMPTION AND ECONOMIC GROWTH – A CASE STUDY OF PAKISTAN

2021 ◽  
Vol 9 (1) ◽  
pp. 139-164
Author(s):  
Saddam Hussain ◽  
Chunjiao Yu
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Energy Consumption ◽  
Causal Relationship ◽  
Inflation Rate ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Series Data ◽  
Relationship Of

This paper explores the causal relationship between energy consumption and economic growth in Pakistan, applying techniques of co-integration and Hsiao’s version of Granger causality, using time series data over the period 1965-2019. Time series data of macroeconomic determi-nants – i.e. energy growth, Foreign Direct Investment (FDI) growth and population growth shows a positive correlation with economic growth while there is no correlation founded be-tween economic growth and inflation rate or Consumer Price Index (CPI). The general conclu-sion of empirical results is that economic growth causes energy consumption.

scholarly journals On the volatility of sensex

2012 ◽  
Vol 1 (1) ◽  
pp. 10-22
Author(s):  
Nateson C ◽  
Suganya D
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
The Other ◽  
Stock Index ◽  
Series Data ◽  
Closing Time ◽  
Market Activity ◽  
Year 2000 ◽  
Daily Returns

The present study seeks to analyse Volatility of popular stock index SENSEX. The present study is based on the closing time series data of SENSEX covering the period from 3rd January 2000, to 30th June 2011. The year 2008 has recorded higher Volatility compared to the other years of the study. Volatility fell in the year 2009 from the high of 2008. The years after were comparatively calmer. In the year 2000, the Volatility was higher signifying enhance market activity. The overall daily Volatility for SENSEX was approximately 1.70 % while the annualized value was approximately 25%-26%. Events Reported around Daily Returns in Excess of +/-5%have also been identified.

scholarly journals ANALISIS DAMPAK KEPEMILIKAN SURAT BERHARGA OLEH BPD TERHADAP PERTUMBUHAN EKONOMI DAERAH

2018 ◽  
Vol 14 (1) ◽  
pp. 32-47
Author(s):  
Khairur dan Telisa Aulia Falian Raziqiin ◽  
Telisa Aulia Falian
Keyword(s):  
Economic Growth ◽  
New York ◽  
Time Series ◽  
Regional Development ◽  
Time Series Data ◽  
Financial Institution ◽  
Positive Influence ◽  
Regional Economic Growth ◽  
Series Data ◽  
Regional Economic

Local government-owned banks (BPD), was established in order to help accelerate the development of the area where the BPD located. The expected goals of this study are: To measure the effect of the placement of funds by BPD on regional economic growth, to measure investment lending by BPD to regional economic growth. Population was all the existing Regional Development Bank in Indonesia. Based on data from Bank Indonesia, the number of regional development banks perDesember 2013 as many as 26 banks. The type of data that will be used in this research is time series data (time series) from January 2009 until December 2013 The model that will be used in this research is the use of panel data. Results of research on Analysis of Impact of Ownership of Securities by BPD Against Regional Development, government capital spending, credit productive, ownership of securities by BPD positive effect on GDP, and significantly affect GDP, labor force have a positive influence on the GDP, but the effect was not significant workforce to GDP.Badan Pusat Statistik. Berbagai tahun. Data Realisasi APBD. Badan PusatStatistik, Jakarta. Bank Indonesia. Berbagai tahun. Laporan Publikasi Bank Umum. Bank Indonesia,Jakarta. Budiono. (2001). Ekonomi Moneter Edisi 3. Yogyakarta : BPFE Djojosubroto, Dono Iskandar. (2004). Koordinasi Kebijakan Fiskal dan Moneter di Indonesia Pasca Undang – undang Bank Indonesia 1999. Jakarta : Kompas Dornbusch, Rudiger, Stanley Fischer, Richard Startz. (2004). Makroekonomi. (Yusuf Wibisono, Roy Indra Mirazudin, terjemahan). Jakarta :MediaGlobal Edukasi. Gujarati, Damodar. (1997). Ekonometrika Dasar. (Sumarno Zein, terjemahan).Jakarta : Erlangga. Gultom, Lukdir. (2013). Tantangan Meningkatkan Efisiensi dan Efektifitas BPD sebagai Regional Champion Dalam Pengembangan Usaha Mikro, Kecil dan Menengah di Indonesia, Makalah SESPIBI Angkatan XXXI (Tidak Dipublikasikan). Bank Indonesia. Husnan, Suad. (2003). Dasar – dasar Teori Portofolio dan Analisis Sekuritas.Yogyakarta : UPP AMP YKPN. Kasmir. (2002). Dasar – Dasar Perbankan. Jakarta : PT. Raja Grafindo Persada. Kuncoro, Mudrajad. (2001) Metode Kuantitatif : Teori dan Aplikasi untuk Bisnis dan Ekonomi. Yogyakarta : AMP YKPN. Latumaerissa dan Julius R. (1999). Mengenal Aspek-aspek Operasi Bank Umum. Jakarta : Bumi Aksara. Lipsey, Richard G, et al. (1997). Pengantar Makro Ekonomi. ( Jaka Wasana danKibrandoko, terjemahan). Jakarta :Binarupa Aksara. Mankiw, Gregory. (2000). Macroeconomics Theory. New York : Worth PublisherInc. Nachrowi, Nachrowi D., Hardius Usman. (2006). Pendekatan Populer dan Praktis EKONOMETRIKA untuk Analisis Ekonomi dan Keuangan.Jakarta : Lembaga Penerbit FEUI. Rahmany, A. Fuad. (2004). Era Baru Kebijakan Fiskal : Pemikiran, Konsep dan Implementasi. Jakarta : Penerbit Buku Kompas, hal. 445 – 462. Rivai, Veithzal, Andria Permata Veithzal, Ferry N. Idroes. (2007). Bank and Financial Institution Management : Conventional & Sharia System, Jakarta : RajaGrafindo Persada. Sunarsip. (2008). Relasi Bank Pembangunan Daerah dan Perekonomian Daerah, dimuat dalam Republika, Rabu, 9 Januari 2008. Rubrik Pareto hal.16 Sunarsip. (2011). Transformasi BPD. Dimuat Infobank Edisi Januari 2011. Republik Indonesia, Kementrian Keuangan (2010), Potensi Bank Pembangunan Daerah Sebagai Pendiri Dana Pensiun Lembaga Keuangan,Tim Studi Potensi Bank Pembangunan Daerah Sebagai Pendiri Dana Pensiun. Jakarta.Waluyanto, Rahmat. (2004). Era Baru Kebijakan Fiskal : Pemikiran, Konsep dan Implementasi. Jakarta : Penerbit Buku Kompas, hal. 463 – 508. Wuryandari, Gantiah. (2013). Mengusung Bank Pembangunan Daerah (BPD) Sebagai Bank Fokus Sektor Strategis Dalam Mendukung Pembangunan Nasional, Makalah SESPIBI Angkatan XXXI (Tidak Dipublikasikan). Bank Indonesia.

Intra-domain and cross-domain transfer learning for time series

2021 ◽  
Author(s):  
Erik Otović ◽  
Marko Njirjak ◽  
Dario Jozinović ◽  
Goran Mauša ◽  
Alberto Michelini ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Transfer Learning ◽  
Time Series Data ◽  
The Other ◽  
Series Data ◽  
Sound Recognition ◽  
Transfer Of Knowledge ◽  
Learning Models ◽  
Machine Learning Models

<p>In this study, we compared the performance of machine learning models trained using transfer learning and those that were trained from scratch - on time series data. Four machine learning models were used for the experiment. Two models were taken from the field of seismology, and the other two are general-purpose models for working with time series data. The accuracy of selected models was systematically observed and analyzed when switching within the same domain of application (seismology), as well as between mutually different domains of application (seismology, speech, medicine, finance). In seismology, we used two databases of local earthquakes (one in counts, and the other with the instrument response removed) and a database of global earthquakes for predicting earthquake magnitude; other datasets targeted classifying spoken words (speech), predicting stock prices (finance) and classifying muscle movement from EMG signals (medicine).<br>In practice, it is very demanding and sometimes impossible to collect datasets of tagged data large enough to successfully train a machine learning model. Therefore, in our experiment, we use reduced data sets of 1,500 and 9,000 data instances to mimic such conditions. Using the same scaled-down datasets, we trained two sets of machine learning models: those that used transfer learning for training and those that were trained from scratch. We compared the performances between pairs of models in order to draw conclusions about the utility of transfer learning. In order to confirm the validity of the obtained results, we repeated the experiments several times and applied statistical tests to confirm the significance of the results. The study shows when, within the set experimental framework, the transfer of knowledge brought improvements in terms of model accuracy and in terms of model convergence rate.<br><br>Our results show that it is possible to achieve better performance and faster convergence by transferring knowledge from the domain of global earthquakes to the domain of local earthquakes; sometimes also vice versa. However, improvements in seismology can sometimes also be achieved by transferring knowledge from medical and audio domains. The results show that the transfer of knowledge between other domains brought even more significant improvements, compared to those within the field of seismology. For example, it has been shown that models in the field of sound recognition have achieved much better performance compared to classical models and that the domain of sound recognition is very compatible with knowledge from other domains. We came to similar conclusions for the domains of medicine and finance. Ultimately, the paper offers suggestions when transfer learning is useful, and the explanations offered can provide a good starting point for knowledge transfer using time series data.</p>

scholarly journals Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy and Food Efficiency Evaluation

2020 ◽  
Vol 17 (11) ◽  
pp. 3891
Author(s):  
Lihua Liu ◽  
Jing Huang ◽  
Huimin Wang
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Coupling Efficiency ◽  
Aggregation Operator ◽  
Visibility Graph ◽  
Series Data ◽  
Efficiency Evaluation ◽  
Geometric Operator ◽  
The Relationship

In the real decision-making process, there are so many time series values that need to be aggregated. In this paper, a visibility graph power geometric (VGPG) aggregation operator is developed, which is based on the complex network and power geometric operator. Time series data are converted into a visibility graph. A visibility matrix is developed to denote the links among different time series values. A new support function based on the distance of two values are proposed to measure the support degree of each other when the two time series values have visibility. The VGPG operator considers not only the relationship but also the similarity degree between two values. Meanwhile, some properties of the VGPG operator are also investigated. Finally, a case study for water, energy, and food coupling efficiency evaluation in China is illustrated to show the effectiveness of the proposed operator. Comparative analysis with the existing research is also offered to show the advantages of the proposed method.

scholarly journals A framework to analyze multiple time series data: A case study with Streptomyces coelicolor

2005 ◽  
Vol 33 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Sarika Mehra ◽  
Wei Lian ◽  
Karthik P. Jayapal ◽  
Salim P. Charaniya ◽  
David H. Sherman ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Streptomyces Coelicolor ◽  
Series Data ◽  
Multiple Time ◽  
Multiple Time Series
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