scholarly journals A Canvas of Data & Indian Card Industry

2017 ◽  
Vol 9 (7) ◽  
pp. 39
Author(s):  
Shounak Ghosh ◽  
Tapomoy Koley
Keyword(s):  
World Bank ◽  
Open Source Software ◽  
Learning Algorithm ◽  
Social Indicators ◽  
Primary Data ◽  
Heat Map ◽  
Reserve Bank ◽  
Data Portal ◽  
Ministry Of Finance ◽  
Reserve Bank Of India

Indian card industry has gone through several interesting changes in the recent past. We wanted to explore this fascinating world both from card issuing and merchant acquiring perspective within our chosen study period of around 6 years - from Q2, 2011 to Q4, 2016. However rather than hunting the data to prove any pre-defined notion we wanted to listen to the data to capture the story it wants to tell us. We took a canvas of raw primary data from a no. of sources ranging from Reserve Bank of India to World Bank, from Ministry of Finance to Ministry of Statistics & Implementation (of Govt. of India) and a no. of other sources like Yahoo Finance, Index Mundi data portal. As a choice of tool we have used R (an open source software) and Excel for our study. In order to uncover the underlying story behind the data we have used an array of techniques ranging from descriptive trend chart, heat map, multidimensional bubble plot, outlier chart to advanced data analytics techniques like clustering using machine learning algorithm. We also uncovered the correlations of card industry parameters with other economic and social indicators and went ahead in building optimum casual predictive model as well as time series forecasting model.

Strategies in Mixed Budget: A Bitopological Approach

2018 ◽  
Vol 15 (01) ◽  
pp. 85-94
Author(s):  
Santanu Acharjee ◽  
Binod Chandra Tripathy
Keyword(s):  
Time Series ◽  
World Bank ◽  
Upper Bounds ◽  
Line Graphs ◽  
Mathematical Tool ◽  
Economic Literature ◽  
Bitopological Space ◽  
Reserve Bank ◽  
Local Functions ◽  
Reserve Bank Of India

The forecasting graphs of World Bank, Reserve Bank of India, etc. are mostly line graphs or time series graphs. Any forecasting contains “standard error” as an error with complicated statistical formulae. A keen observation shows that mathematical patterns are available in nature, but in most of the cases, it is difficult for us to recognize these patterns. Similarly, it is most important for us to know the least upper bounds of these line graphs or time series graphs so that peaks of the prices with respect to time will not exceed these least upper bounds. It is hard to find any statistical or mathematical tool to determine these least upper bounds. Thus we give methodology to obtain these least upper bounds. We show existence of an equilibrium between the expected price and the original price of a commodity with the help of local functions and expansion operators of a bitopological space. These methods are based on choice of a consumer. Examples are provided to show that price of a commodity cannot exceed the interval of expected price. Moreover, we try to provide possible answers to the problem of “Control of Economic Variable” of Morgenstern [O. Morgenstern, Thirteen critical points in contemporary economic theory: An interpretation, Journal of Economic Literature 10(4) 1972 1163–1189] by determining least upper bounds.

Eko: The Mobile Phone as a Financial Identity

2014 ◽  
Vol 18 (01) ◽  
pp. 143-173
Author(s):  
Kavitha Ranganathan ◽  
Amit Kapoor
Keyword(s):  
Open Source Software ◽  
Financial Services ◽  
Low Cost ◽  
Bottom Of The Pyramid ◽  
Reserve Bank ◽  
Start Up ◽  
Banking Institutions ◽  
The Masses ◽  
Technology Solution ◽  
Reserve Bank Of India

Eko Financial Service Private Limited is a young Indian start-up that uses mobile technology for bringing banking to the bottom of the pyramid market. Eko leverages the Banking Correspondent model propagated by the Reserve Bank of India, to provide bank accounts and remittance services for those who have been excluded from the formal banking institutions. With an innovative low-cost technology solution which uses open-source software and cloud computing, the case illustrates how Eko hopes to leverage the mobile revolution sweeping the country to provide financial services to the masses.

scholarly journals Why are the pepper prices declining? An analysis of changing production and trade scenario in India

2020 ◽  
pp. 60-69
Author(s):  
A.G. Adeeth Cariappa ◽  
B.S. Chandel
Keyword(s):  
World Bank ◽  
Secondary Data ◽  
International Market ◽  
Farming Community ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Reserve Bank ◽  
Major Player ◽  
Domestic Prices ◽  
Reserve Bank Of India

During the 1950s, India was the major player in the pepper market. Recently India has dropped to 4th position in production and exports. The price per kilogram of pepper in Cochin market reduced from ` 687 to ` 383 between 2014-15 and 2018-19. This manuscript attempts to study the reasons for the decline in India’s share in world pepper market and the recent fall in prices. The secondary data from the Food and Agriculture Organization, World Bank - World Integrated Trade Solutions, Reserve Bank of India and Spices Board of India were used for analysis. Transitional probability matrix was deployed to analyse the change in the direction of trade, relative comparative advantage and competitive index was used to study India’s market power in the international market. There has been a change in the direction of trade since 1999-2000. The results revealed a four per cent decline in area under pepper during 2000-2018, and now Indian pepper market has become import oriented with a CAGR in imports of 13 per cent during 1981 to 2000 and four per cent during 2001 to 2016. A similar trend was observed in production and exports as it got reduced from 25 per cent and 20 per cent in 1960s to ten per cent and five per cent respectively, in 2016. Increased supply in the international market, decreased production, cheaper imports and illegal imports have pulled down the domestic prices sharply in recent years. From 1995, workers’ wages have increased by around 10 per cent, and with decreasing prices, the Indian pepper industry looks grim. Appropriate policies to safeguard Indian farmers’ interest, such as export promotions, increasing productivity, delivering reasonable prices and incentives for processors would instil confidence in the farming community and the industry as a whole.

scholarly journals An Examination of India-South Korea Bilateral Investment Relations

2021 ◽  
pp. 337-344
Author(s):  
Mr. Nilesh S. Mhatre
Keyword(s):  
Economic Development ◽  
South Korea ◽  
Foreign Investment ◽  
Direct Investment ◽  
Financial Resource ◽  
Quarter Century ◽  
Reserve Bank ◽  
Ministry Of Finance ◽  
International Investors ◽  
Reserve Bank Of India

Foreign investment has accelerated at an incredible rate over the last quarter-century, and alterations in the flow of this investment are increasingly changing the global economic environment. International investors provide new markets not only new capital, technology, competitive spirit, and ideas, but also additional jobs. For India's economic development, foreign direct investment (FDI) has been a substantial non-debt financial resource and a key growth engine. South Korea's economy is one of Asia's most promising and lively. The country's stability, quick growth rates, strong manufacturing base, export focus, and availability of superior technology make it an appealing investment destination. India's permitted cumulative investments in South Korea from April 1996 to December 2019 was US$ 593.9 million, according to data from the Ministry of Finance, Government of India (GOI), and the Reserve Bank of India (RBI). According to the FDI Markets database, India was the 15th largest investor in South Korea between 2009 and 2019, with 14 Indian businesses investing US$ 913 million in 17 FDI projects, resulting in the creation of 5,519 jobs. As a result, the current study examines India-South Korea's bilateral investment ties and looks ahead to possible areas of cooperation in the future between the two countries' investment relations.

scholarly journals PENGHITUNGAN KREDIT PAJAK MASUKAN PKP YANG MELAKUKAN PENYERAHAN YANG TERUTANG PPN DAN YANG DIBEBASKAN (STUDI PADA PDAM TIRTA PATRIOT)

2020 ◽  
Vol 3 (2) ◽  
pp. 60-69
Author(s):  
Rizqi Haniyah ◽  
Asqolani Asqolani
Keyword(s):  
Government Regulation ◽  
Value Added ◽  
Field Research ◽  
Primary Data ◽  
Clean Water ◽  
Value Added Tax ◽  
Library Research ◽  
Water Value ◽  
Ministry Of Finance ◽  
One Year

Perusahaan Daerah Air Minum (PDAM) pada umumnya memiliki dua jenis penghasilan yaitu layanan penyediaan air bersih sebagai sumber utama penghasilannya dan penghasilan non air. Air bersih baik yang bisa diminum atau tidak, merupakan Barang Kena Pajak yang dibebaskan dari pengenaan Pajak Pertambahan Nilai sesuai Peraturan Pemerintah Nomor 40 Tahun 2015. Disamping itu, perusahaan juga memiliki penghasilan lain yang secara ketentuan perpajakan terutang pemungutan PPN. Namun di sisi lain, terdapat permasalahan terkait Pajak Masukan yang seharusnya tidak dapat dikreditkan seluruhnya karena terdapat penyerahan yang terutang pajak namun tidak dapat diketahui dengan pasti. Oleh sebab itu jumlah Pajak Masukan yang dapat dikreditkan untuk penyerahan yang terutang pajak dihitung dengan menggunakan pedoman yang diatur dengan Peraturan Menteri Keuangan No. 135/PMK.011/2014. Penelitian ini menggunakan metode kualitatif yang ditujukan untuk memperoleh data dan fakta tentang kasus pengkreditan Pajak Masukan dengan menggunakan data primer yaitu wawancara. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah Studi Kepustakaan (Library Research) dan Studi Lapangan (Field Research). Kesimpulan dari penelitian ini adalah adanya Pajak Masukan yang seharusnya tidak seluruhnya dikreditkan karena terdapat penyerahan yang digunakan secara bersama-sama untuk menghasilkan air bersih (BKP yang dibebaskan) dan penerimaan non air bersih (BKP) dan tidak dapat diketahui secara pasti jumlahnya. Pengkreditannya seharusnya dilakukan dengan menggunakan penghitungan kembali Pajak Masukan berdasarkan perkiraan setelah diketahui nilai penyerahan terutang dan tidak terutang Pajak Pertambahan Nilai dibebaskan selama satu tahun.Kata kunci: Pengkreditan Pajak Masukan, Air Bersih, Pajak Pertambahan Nilai, Barang Kena Pajak Dibebaskan. AbstractThe company of Regional Drinking Water (PDAM) generally has two types of income, namely the clean water supply service as the main source income and non-water income. Clean water that can be drunk or not, is a taxable good that is exempt from the imposition of value added tax according to government regulation number 40 year 2015. On the other hand, the company also has other income that is based on taxation payable VAT. But there are issues related to input tax that should not be credited entirely because there is a tax payable submission but cannot be identified with certainty. Therefore, the amount of input tax which can be credited for the value-added reporting is calculated using the guidelines governed by the Ministry of Finance regulation No. 135/PMK. 011/2014. This Research uses qualitative methods aimed at obtaining data and facts about the case of tax crediting of inputs using primary data i.e. interviews. The data collection techniques used in the study Library Research and field research. The conclusion of the study is that the input tax for some inventories should not be fully credited because they are used to produce clean water (freetax) and non-water income (taxable goods) and can not be exactly identified. The credit should be made by using an estimated tax return calculation after all the income is reported for one year. Keywords: Input tax, Clean Water, Value Added Tax, Free-Taxable Goods.

scholarly journals STUDY OF THE DISTRIBUTION OF WEALTH IN THE MIDDLE AND TOP SEGMENTS OF THE POPULATION OF GEORGIA

2019 ◽  
Vol 4 (7) ◽  
pp. 130-142
Author(s):  
QETEVAN PIPIA
Keyword(s):  
Normal Distribution ◽  
World Bank ◽  
Lognormal Distribution ◽  
Pareto Distribution ◽  
Population Distribution ◽  
Distribution Data ◽  
Distribution Of Wealth ◽  
The World Bank ◽  
Ministry Of Finance ◽  
Laws Of Distribution

Due to economic, social, political and other differences, different sectors of society are subject to different laws of distribution. Among these laws are Pareto distribution, the normal distribution, the lognormal distribution, and so on. It is noteworthy that the higher, richer stratum of a society more often depends on the Pareto distribution. As for the poor and middle class, there was an attempt to build their model using a normal distribution. But later it turned out that more accurate results are provided by a lognormal distribution. The article attempts to build a model of the distribution of the upper layers of the population of Georgia in terms of per capita GDP consumption (according to the World Bank) using Pareto distribution. As for the other layers, due to the lack of data in GeoStat, when trying to build a model using a lognormal distribution, data on the population’s declared income are used, obtained from the Revenue Service of the Ministry of Finance of Georgia, hoping that this data correlates with the population distribution by GDP consumption.

scholarly journals The Monetary Crisis and Foundation for Reserve Bank of India (1890-1935)

2020 ◽  
Author(s):  
M. Balaji
Keyword(s):  
World War I ◽  
Interwar Period ◽  
Banking System ◽  
Economic Interest ◽  
Stabilization Policy ◽  
British India ◽  
World War ◽  
Reserve Bank ◽  
The World ◽  
Reserve Bank Of India

The monetary policy of British India was highly controversial during the interwar period as it aimed to protect the budgetary obligations and private commerce. The currency stabilization policy was seen as a tool to protect the British economic interest while they ruled India. The currency came under serious pressure during the World War I and Great depression, the facets of Indian currency’s dependence was exposed through the modified council bill system and Gold exchange standard. The much-needed currency reforms and banking system were conceded by the colonial administration after much wrangling for half a century.

scholarly journals RESOURCES PROVIDING DATA FOR MACHINE LEARNING AND TESTING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

2021 ◽  
pp. 39-52
Author(s):  
Денис Валерьевич Сикулер
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
World Bank ◽  
Open Data ◽  
Data Access ◽  
Free Access ◽  
Internet Resources ◽  
Data Registry ◽  
Data Portal ◽  
Access To Data

В статье выполнен обзор 10 ресурсов сети Интернет, позволяющих подобрать данные для разнообразных задач, связанных с машинным обучением и искусственным интеллектом. Рассмотрены как широко известные сайты (например, Kaggle, Registry of Open Data on AWS), так и менее популярные или узкоспециализированные ресурсы (к примеру, The Big Bad NLP Database, Common Crawl). Все ресурсы предоставляют бесплатный доступ к данным, в большинстве случаев для этого даже не требуется регистрация. Для каждого ресурса указаны характеристики и особенности, касающиеся поиска и получения наборов данных. В работе представлены следующие сайты: Kaggle, Google Research, Microsoft Research Open Data, Registry of Open Data on AWS, Harvard Dataverse Repository, Zenodo, Портал открытых данных Российской Федерации, World Bank, The Big Bad NLP Database, Common Crawl. The work presents review of 10 Internet resources that can be used to find data for different tasks related to machine learning and artificial intelligence. There were examined some popular sites (like Kaggle, Registry of Open Data on AWS) and some less known and specific ones (like The Big Bad NLP Database, Common Crawl). All included resources provide free access to data. Moreover in most cases registration is not needed for data access. Main features are specified for every examined resource, including regarding data search and access. The following sites are included in the review: Kaggle, Google Research, Microsoft Research Open Data, Registry of Open Data on AWS, Harvard Dataverse Repository, Zenodo, Open Data portal of the Russian Federation, World Bank, The Big Bad NLP Database, Common Crawl.

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