As of 2021, Russia held natural resources amounting to an estimated total value of ** trillion U.S. dollars. This figure includes the value of Russia’s many valuable natural resources, which includes coal, oil, natural gas, gold, timber, and rare earth metals, among others. Natural Resources Natural resources can be defined as resources that occur naturally and exist independently from the actions of humans. They are commonly categorized in biotic and abiotic resources, where biotic refers to living and organic materials (such as plants), and abiotic resources to refers to non-living materials (such as minerals). Furthermore, natural resources can be divided into the categories of renewable and non-renewable. Renewable resources such as wind, sunlight, and forests are not permanently depleted when we consume or utilize them. Conversely, non-renewable resources are available in finite quantities and can be permanently depleted because of this. Among the most prominently known non-renewable resources on Earth are fossil fuels such as coal, natural gas, and petroleum, usually exploited by humankind to generate energy. Natural resources and sustainability The value of natural resources is often determined by their scarcity and by their value for our modern economies. In the consumption-oriented, globalized world, industries need to balance meeting consumer demands and guaranteeing business growth while not over-exploiting and consequently depleting the natural resources of our planet. With natural resources having such high economic value and demand, in addition to the fact that many countries in the world have heavily resource-based economies, the socially, environmentally, and economically sustainable management of these resources is often an afterthought, if its considered at all. This issue is increasingly causing environmental issues, however, and more attention is now being paid by national governments and international environmental watch groups, as a result. Natural resources in the United States With a total natural resource value of ** trillion U.S. dollars, the U.S. is the second leading country worldwide based on natural resource value after Russia. Among the main contributors to the United States’ natural resource value are coal, timber, natural gas, gold, and copper. These industries have strong historic significance for the United States. The U.S. lumber industry, for example, originated during the colonial era, when importing timber from the United States saved people in the U.K. from cold winters. Nowadays, U.S. timber is mostly used for the production of pulp and paper, as well as furniture. The U.S. also has the largest proven coal reserves worldwide as of 2019. In 2020, the U.S. also accounted for *** percent of global coal production, which made the country the fifth-largest coal producer in the world.

This statistic shows the gross domestic product (GDP) per capita in Russia from 1997 to 2024, with projections up until 2030. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. In 2024, the GDP per capita in Russia was around 14,794.7 U.S. dollars. See the Russian GDP for comparison. Russia's wealth Russia generates most of its wealth through its energy sector, given that a large percentage of its industrial and agricultural sectors have been privatized in the 1990s. The majority of Russia’s exports consisted of natural resources, such as oil, gas and metals. Russia’s primary export partners are located within Europe, with the exception of China, and are often the recipients of a large amount of Russia’s natural gas exports. The country’s second most important and influential sector is the military sector, due to having built up a complex arms industry and having the proficiency to produce high tech weapons. Russia ranks as one of the highest spenders for military production and is one of the more intimidating military powers in the world. Due to the privatization of Russia’s industrial and agricultural sectors, a rather large part of the population was able to capitalize on the market. Russia is home to one of the highest numbers of billionaires in the world, trailing only countries such as the United States and China.

Russia RU: GDP: % of GDP: Gross Value Added: Industry data was reported at 30.648 % in 2023. This records a decrease from the previous number of 32.096 % for 2022. Russia RU: GDP: % of GDP: Gross Value Added: Industry data is updated yearly, averaging 31.780 % from Dec 1989 (Median) to 2023, with 35 observations. The data reached an all-time high of 46.597 % in 1989 and a record low of 27.932 % in 2014. Russia RU: GDP: % of GDP: Gross Value Added: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Share of GDP. Industry (including construction) corresponds to ISIC divisions 05-43 and includes manufacturing (ISIC divisions 10-33). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4. Note: For VAB countries, gross value added at factor cost is used as the denominator.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;Note: Data for OECD countries are based on ISIC, revision 4.

This page displays a table with Russia Exports By Category in U.S. dollars, according to the United Nations COMTRADE database on international trade.

RU: GDP: USD: Gross Value Added at Factor Cost: Services data was reported at 886.317 USD bn in 2017. This records an increase from the previous number of 727.419 USD bn for 2016. RU: GDP: USD: Gross Value Added at Factor Cost: Services data is updated yearly, averaging 231.602 USD bn from Dec 1989 (Median) to 2017, with 29 observations. The data reached an all-time high of 1,285.621 USD bn in 2013 and a record low of 97.738 USD bn in 1999. RU: GDP: USD: Gross Value Added at Factor Cost: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Nominal. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total; Note: Data for OECD countries are based on ISIC, revision 4.

Russia RU: GDP: Growth: Gross Value Added: Agriculture, Forestry, and Fishing data was reported at 6.650 % in 2022. This records an increase from the previous number of -0.825 % for 2021. Russia RU: GDP: Growth: Gross Value Added: Agriculture, Forestry, and Fishing data is updated yearly, averaging 1.577 % from Dec 1991 (Median) to 2022, with 32 observations. The data reached an all-time high of 17.100 % in 1999 and a record low of -18.800 % in 1998. Russia RU: GDP: Growth: Gross Value Added: Agriculture, Forestry, and Fishing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual growth rate for agricultural, forestry, and fishing value added based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. Agriculture corresponds to ISIC divisions 01-03 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 4.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;Note: Data for OECD countries are based on ISIC, revision 4.

This statistic shows the gross domestic product (GDP) per capita in Russia from 1997 to 2024, with projections up until 2030. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. In 2024, the GDP per capita in Russia was around 14,794.7 U.S. dollars. See the Russian GDP for comparison. Russia's wealth Russia generates most of its wealth through its energy sector, given that a large percentage of its industrial and agricultural sectors have been privatized in the 1990s. The majority of Russia’s exports consisted of natural resources, such as oil, gas and metals. Russia’s primary export partners are located within Europe, with the exception of China, and are often the recipients of a large amount of Russia’s natural gas exports. The country’s second most important and influential sector is the military sector, due to having built up a complex arms industry and having the proficiency to produce high tech weapons. Russia ranks as one of the highest spenders for military production and is one of the more intimidating military powers in the world. Due to the privatization of Russia’s industrial and agricultural sectors, a rather large part of the population was able to capitalize on the market. Russia is home to one of the highest numbers of billionaires in the world, trailing only countries such as the United States and China.

The statistic shows the distribution of the workforce across economic sectors in Russia from 2013 to 2023. In 2023, 5.69 percent of the workforce in Russia was employed in agriculture, 26.38 percent in industry and 67.93 percent in services. Russia’s economy The majority of Russia’s labor force works in the services sector, which accounts for more than half of the jobs in the country. About 30 percent work in the industry sector and the rest in agriculture. Interestingly, Russia is among the leading export countries worldwide and agricultural products, as well as meat, are among the main exported goods. Russia’s economy also profits significantly from selling and exporting fish and sea food. Due to large oil resources, Russia is also among the largest economies and the countries with the largest gross domestic product / GDP worldwide. Subsequently, living and working conditions in Russia should be above average, but for a long time, many Russians have struggled to get by. While conditions seem to improve nowadays, many Russians still live below the poverty line. One suggested reason for this is corruption, which has been cited as a severe problem for the country for a long time, and continues to pose difficulties for Russia’s economy. Illicit employment and the so-called “shadow economy”, which does not officially contribute to the fiscal system, yields amounts worth almost half of Russia’s gross domestic product. This can be seen on a ranking of the untaxed economy in selected countries as a share of GDP. In addition to oil, fish and agricultural products, Russia also manufactures and exports arms and weapons. It is ranked third among the countries with the highest military spending, and second among the countries, in which military spending accounts for a significant percentage of the gross domestic product.

RU: GDP: Gross Value Added at Factor Cost: Services data was reported at 51,710,241.431 RUB mn in 2017. This records an increase from the previous number of 48,777,752.050 RUB mn for 2016. RU: GDP: Gross Value Added at Factor Cost: Services data is updated yearly, averaging 7,108,335.281 RUB mn from Dec 1989 (Median) to 2017, with 29 observations. The data reached an all-time high of 51,710,241.431 RUB mn in 2017 and a record low of 175.300 RUB mn in 1989. RU: GDP: Gross Value Added at Factor Cost: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Nominal. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ; Note: Data for OECD countries are based on ISIC, revision 4.

This graph shows the growth in the U.S. import volume of trade goods from Russia from 1992 to 2023. In 2023, U.S. imports from Russia amounted to approximately 4.57 billion U.S. dollars. RussiaRussia's foreign trade balance of goods generated a surplus of about 187 billion U.S. dollars, with more resulting from exports than imports in 2014. Russia exported trade goods valued about 418.8 billion U.S. dollars in 2019. In a global ranking of national exports, Russia was sixteenth. Leading exporters like China, the United States, and Germany are exporting goods worth between 1.5 and 2.5 trillion U.S. dollars. The placement of Russia’s export ranking is linear with its placement on the ranking of the biggest economies in the world. Russia had the eleventh largest GDP worldwide with about 1.6 trillion U.S. dollars in 2019. Russia's most important export countries are mostly its direct neighbors, like China, Ukraine, Belarus, Poland, and Kazakhstan. About 35 percent of all exports go to neighboring countries. China is the most important country within the aforementioned nations, which takes about 8 percent of Russia's exported goods. The United States are not among the top ten. The nation sits in twelfth place of Russia's export destinations, with about three percent. The products exported from Russia are unsurprisingly mainly mineral products and metals, with crude and refined petroleum making up for 54 percent of all exports. The main export product apart from resources is wheat. Exported wheat from Russia was valued at about 6.2 billion U.S. dollars in 2012. Russia is one of the principal wheat exporters. Although the development of Russia's exports has been somewhat positive in recent years, the political crisis with the Ukraine, resulting in economic sanctions applied by important trade countries like Germany, the EU, the United States and many others, might have dampened foreign trade altogether. The result was a negative growth in exports of about five percent in 2014.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

This survey covers the Russian Federation.

Analysis unit

• Household
• Individual

Universe

The WVS for the Russian Federation covers national population, aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not an upper age cut-off for the sample. Population: Total non-institutionalized population of the Russian Federation, 18 years and older, without citizens living in the Far North and in inaccessible regions of Siberia.

Five-stage area probability sample: (1) The country is divided into 4 strata. For each stratum the desired number of respondents is defined proportional to population size. (2) Within each stratum 50 primary sampling units (administrative districts) are selected at random proportional to size. (3) Within each primary sampling unit secondary sampling units (towns and rural Soviets as administrative subdistricts) are selected randomly (4) Within each secondary sampling unit third sampling units (voting districts in the towns, villages belonging to a rural Soviet in the rural areas) are randomly selected. The total number of third sampling units was 186. (5) Within each third sampling unit households were selected at random from a household register (fourth sampling unit). (6) Within each household the respondent is randomly selected using the "Kish-selection-grid": all adult family members are listed in a certain order, first males from the oldest to the youngest, than females from the oldest to the youngest; the respondent is selected by a selection key which is randomly composed for each possible type of household composition (fifth sampling unit). Selection is done: 41% Male and 59% Female. 75% Urban and 25% Rural. The sample size is N=2040.

Universe: The universe includes the adult population of Russia residing in 89 regios and republics. The Far North and inaccessible regions of Siberia, military bases and prisons are not included. Primary sampling units: Administrative rayons in regions, krays and republics are used as the primary sampling units (PSUs). Each rayon is a geographically localized territory which in general contains both urban and rural settlements. Either a town or a rural settlement may be a center of rayon. Usually, but not always, it is the largest settlement in a rayon. If a rural settlement is the center of a rayon itself generally consists only of rural settlements and is referred to the category of rural rayhons. Separate towns which are considered by official statistical institutions as rayons are also included in the set of primary sampling units. These towns are not part of rayons though they are situated in the rayon's territory. Sometimes they may also include some suburbs. So separate towns and rural rayons may be considered as two poles of a scale which contains all various rayhons of Russia (primary sampling units, PSUs). On the continuum between these poles there are rayons of mixed type containing urban and rural sttlements of different sizes. Population size of different rayons may vary from 4-5 thousand to several hundred thousand or even several million of people in cities considered as separate rayons. If population size is less than 10.000 the rayon is linked to an adjacent one in a stratum. All PSUs are presented in the form of data base of more than 2.000 records with each record corresponding to one rayon or separate town (later referred to as rayons). The record for each rayon (PSU) contains the following data: - unique identification number and rayon title, - code and title of a region, - central town population size, - rayon population size All data are based on annual statistical reports (Chislennost RSFSR na 1 janvarya 1990) and 1989 census information. Primary sampling units stratification: PSUs stratification is based on two variables: geographical placement and status of the rayon center. All primary sampling units are grouped in strata consisting of homogeneous rayons. Strata are formed so that each stratum has approximately the same population size. They may consist of from one to several dozen PSUs depending on PSUs population size. In this sample the stratum population size is equal approximately 3.000 thousand (tab.1). Two cities in Russia Moscow and St. Petersburg have population size exceeding stratum population size. They form so called self-representing strata. The geographic placement of a rayon is defined by corresponding economic and geographic zone. According to statistical institutions Russia is divided into 11 economic and geopraphic regions. But for sample construction this division seems to be too fractional and can prevent forming strata of equal size in each zone. The main goal for using the geographic factor as a stratification variable is the uniform spreading of PSUs through Russia territory. For these reasons economic and geographic regions in Russia wre grouped in four zones:

• Zone 1 - North and Center of European part of Russia (unites Northern, North Western + Kaliningrad obl., Central and Volgo-´Vjatsky regions of Russia).

• Zone 2 - South of Wuropean part of Russia (unites Tsentralno-Chernozjemny, Povolzhsky and North- Caucasian regions of Russia).

• Zone 3 - Ural and West Siberia (two economic regions)

• Zone 4 - East Siberia and Far East (two economic regions). For economic and geographic division in Russia seven factors are used: nature and resources, population, industry, power engineering, area industry distribution, agriculture, transport and communicftions ( Economicheskaya geographiya SSSR. Moskva, Vishaya shkola, 1983). 11 regions were aggregated in four zones on the basis of two first factors: nature and resources and population. The second variable of PSUs stratification is the status of the rayon center. It is formed on officially accepted statistical classification by type and population size:

• rural settlement,

• urban settlement with populatiton size:

  • below 20.000
  • between 20.000 and 50.000
  • between 50.000 and 200.000
  • between 500.000 and 1000.000
  • more than 1000.000

Remarks about sampling: - Final numbers of clusters or sampling points: 186 - Sample unit from office sampling: Household

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was in Russian. Some special variable labels have been included, such as: V56 Neighbours: Jews and V149 Institution: The European Union. Special categories labels are: V203/ V204: Geographical affinity, 1. Locality or town where you live, 2. Region of country where you live, 3. Own country as a whole, 4. Europe, 5. The world as whole. Country Specific variables included are: V208: Ethnic identification, 2. Ukranian, 3. Tatarian 4. Komi 5 Mordovia, 6 Karbardian 7 Balkarian; V209: Language at home: 2. Ukranian, 3. Tatarian 4. Komi 5 Mordovia, 6 Karbardian 7 Balkarian; The variables political parties V210 a V212; Region: V 234 and V206 Born in this country are also included as country specific variables. The ethnic group of the respondent was not asked in the interview. In the cases of Eastern Europe Countries where the ethnic group is missing the language chosen for interview is the only indicator available to control the ethnic composition of the samples. Nevertheless, native language indicated in the cesus of 1989 and language chosen for interview are not exactly the same, since the first is rather differentiated whereas for the last the alternatives to choose between where only the national language or Russian.

Response rate

The response rate for the Russian Federation is 74.9% and is calculated as follows: (2040/2723) x 100=74.9%

Sampling error estimates

+/- 2,2%

This data collection consists of transcripts from 12 focus group discussions on themes related to social equality in Russia. The focus group discussions were conducted by the Institute of Applied Politics in Moscow, directed by Dr Kryshtanovskaya; using a discussion guide written by the Investigators. They were held in 12 cities chosen to represent different regions of the country, with an emphasis on provincial cities: Ufa, Kaliningrad, Ekaterinburg, Tiumen, Saratov, Ulyanovsk, Volgograd, Ivanovo, Irkutsk, Obolensk, Vladivostok and Protvino. The respondents included a mix of ages, genders, blue and white collar workers. The focus groups in Protvino and Ulyanovsk were held only for respondents age 18-29.

The focus group discussions dealt with household and national economic change, perceptions of social fairness, and welfare values. Specifically, respondents were asked about the state of the national and local economies, their household economy, how they define rich and poor people and how they position themselves in relation to these categories. They were asked about whether they perceived differences in wealth between individuals, regions and between urban and rural areas as fair, and whether such differences are increasing or decreasing. Finally they were asked about whether the rich should take more responsibility for the welfare of the poor, about their own personal responsibility and that of the state and businesses, as well as about progressive income taxes and the degree to which the state should control the economy. The discussion guide is provided in Russian and English.

Basic information about the respondents, including gender, age, and occupation are provided at the top of each focus group transcript. Each participant is identified by their given name only.

The transcripts are provided in Russian. The Russian text was transcribed by the Institute of Applied Politics from audio files.

A parallel set of focus groups was conducted in China and are available as the collection Social equality forum China: Focus group transcripts (see Related Resources).

Taken together, Russia and China account for 41 per cent of the total territory of the BRICs and 63 per cent of their GDP/PPP. On Goldman Sachs projections China will be the world’s largest economy by 2050, and Russia its sixth largest. The project will seek to examine the following propositions: (1) that these two BRIC countries are becoming increasingly unequal; (2) that within them, political power and economic advantage are increasingly closely associated; (3) that their political systems have increasingly been employed to ensure that no effective challenge can be mounted to that combination of government position and economic advantage; (4) that set against a broader comparative perspective, an increasingly unequal society in which government is effectively immune from conventional challenge is likely to become increasingly regressive, or unstable, or both. Evidence will be drawn from official statistics, interviews with policy specialists and government officials, two dozen focus groups, and an analysis of the composition of the management boards of the largest companies in both countries. A final part of the analysis will employ crossnational evidence to test a series of hypotheses relating to the association between inequality and political instability on a more broadly comparative basis.

Russia email data connects you directly to high-value contacts, fueling your sales pipeline and strengthening your market position. At List to Data, we provide precise Russian email data to support your marketing growth. This resource includes a verified directory for efficient outreach. Transition your campaigns with reliable datasets that connect you to businesses and consumers. Use this material to optimize engagement and drive measurable results. Whether for B2B or B2C, our leads deliver success. With a focus on accuracy, enhance communication with potential customers. This library is your key to expanding your market reach. Trust List to Data for quality email solutions in Russia. Russia consumer email list delivers quick access to high-value contacts, empowering your efforts and increasing conversion rates. Access the Russian market with our premium Russian consumer email list. This comprehensive resource provides access to a vast network of potential customers. As a result, you can increase your brand visibility and drive sales. Moreover, our data is regularly updated and verified. Therefore, you can improve your marketing ROI. Consequently, you can target specific demographics and regions. Furthermore, this valuable resource allows you to connect with key decision-makers. Finally, List to Data offers this powerful dataset to fuel your business growth in Russia. Russia business email list is a valuable resource for reaching professionals in Russia. This database offers verified leads to ensure your campaigns are targeted and effective. Additionally, it is designed to save time and effort. Moreover, the directory is regularly updated for accuracy. Furthermore, it provides a seamless way to expand your market reach. As a result, you can boost engagement and drive growth. In addition, this library of contacts is ideal for B2B and B2C outreach. Finally, trust List To Data to deliver a dataset that enhances your marketing efforts and delivers measurable results.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 213 companies listed on the Moscow Exchange MICEX-RTS (MISX) in Russia. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Russia:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Russia:

Moscow Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Moscow Exchange. This index provides an overview of the overall market performance in Russia.

Moscow Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Moscow Exchange. This index reflects the performance of international companies operating in Russia.

Company A: A prominent Russian company with diversified operations across various sectors, such as energy, technology, or finance. This company's stock is widely traded on the Moscow Exchange.

Company B: A leading financial institution in Russia, offering banking, insurance, or investment services. This company's stock is actively traded on the Moscow Exchange.

Company C: A major player in the Russian natural resources or manufacturing sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Moscow Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Russia, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Russia ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Russia?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Russia exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and wire transfers, facilitating a convenient and secure payment proces...

Together with the Russian Academy of Sciences, IIASA's Forestry (FOR) project has released a CD-ROM titled Land Resources of Russia, Version 1.1, containing socioeconomic and biophysical data sets on important targets of international conventions — climate change, wetlands, desertification, and biodiversity. The CD-ROM, a country-scale integrated information system, supports sustainable use of land resources in line with Chapter 10 of Agenda 21 (UNCED) and makes a contribution to the Rio+10 Summit.

The Project's analysis of land resources are crucial for doing full greenhouse gas (or carbon) accounting. Integrated land analyses are also important for the introduction of sustainable forest management. FOR's land analyses concentrate on Russia, which is used as a case study for full carbon and greenhouse accounting.

Russia's area of forests, called here the forest zone, covers about 1180 million ha or 69% of the land of the country. The forested area (forests forming closed stands) occupies some 765 million ha constituting 65% of the forest zone. Forests are elements of a land-cover mosaic that direct the features of landscapes, ecosystems, vegetation and land uses. The FOR project attempts to overcome the traditional approach of just considering the direct utilities of forests. Instead, FOR operates with a holistic view of forests in a fully-fledged land concept. Integrated analysis of the land requires extended databases that includes various data for the total land operated in the form of GIS-based tools.

The land databases on Russia are the most comprehensive ever assembled, inside or outside of Russia. The databases have been enriched by remotely sensed data, biogeochemical functionality (carbon analysis), and institutional frameworks. The data included on the CD-ROM have been specially selected and filtered to meet the following criteria: (1) completeness: to meet a variety of the analysis tasks; (2) complexity: to describe a diversity of the task aspects; (3) consistency: to provide compatible results; to be ata compatible scale and, to provide a compatible time horizon; and (4) uniformity: to allow them to be standardized and formatted according to modern data handling routines.

The following databases and coverages are included on the CD-ROM and are available for download:

Socioeconomic Database -- Describes the social environment of each administrative region in Russia with close to 7000 parameters. The data cover the years 1987-1993. Coverages in this section include:

(1) Socioeconomic Statistical Database. This database provides the following statistical data sets: Population; Labor and Salary; Industry; Agriculture; Capital Construction; Communication and Transport; State Trade and Catering; Utilities and Services; Health Care and Sport; Education and Culture; Finance; Public Consumption; Industrial Production; Interregional Trade; Labor Resources; Supply of Materials; Environmental Protection; Foreign Trade; and Price Indices.

(2) Population Database. Adapted from Center for International Earth Science Information Network (CIESIN), Columbia University; International Food Policy Research Institute (IFPRI); and World Resources Institute (WRI). 2000. Gridded Population of the World (GPW), Version 2, this coverage contains population densities for 1995 on a 2.5 degree grid. Data were adjusted to match United Nations national population estimates for 1995.

(3) Administrative Oblasts, Cities & Towns Database. Oblasts coverage contains 92 polygons, 88 of which contain Oblast names, the other four represent waterbodies. The cities coverage contains 37 cities identified by name.

(4) Transportation Database. The statistical data sets and maps cover the transport routes of the railway, road, and river networks spanning the entire country. Railways and roads are classified by type and status, and major rivers are named. Map coverages (line data) were created from the Digital Chart of the World, using the 1993 version at the 1:1,000,000 scale.

Natural Conditions Database. This section of the CD-ROM contains the basic land characteristics. This database provides specialists and scientists in research institutes and international agencies with the capability to perform scientific analysis with a Geographic Information System. These data describe land characteristics that might be applied in various ways, such as individual items (e.g., temperature, elevation, vegetation community, etc.), in combination (e.g., forest-temperature associations, soil spectra for land use types, etc.), and as aggregations based on a conceptual framework of a different level of complexity (e.g., ecosystem establishment, human-induced land cover transformation, biochemical cycle analysis, etc.). Coverage includes:

(1) Climate Database. Temperature (annual and seasonal) and Precipitation... Visit https://dataone.org/datasets/Land_Resources_of_Russia%2C_Version_1.1.xml for complete metadata about this dataset.

RU: GDP: Real: Gross Value Added at Factor Cost: Services data was reported at 49,807,635.306 RUB mn in 2017. This records an increase from the previous number of 48,777,752.050 RUB mn for 2016. RU: GDP: Real: Gross Value Added at Factor Cost: Services data is updated yearly, averaging 35,143,300.291 RUB mn from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 50,305,892.112 RUB mn in 2014 and a record low of 23,041,593.384 RUB mn in 1998. RU: GDP: Real: Gross Value Added at Factor Cost: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Real. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges and import duties. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in constant local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ; Note: Data for OECD countries are based on ISIC, revision 4.

The presented database is a set of hydrological, meteorological, environmental and geometric values for Russia Federation for the period from 2008 to 2020.

Database consist of next items:

• Point geometry for hydrological observation stations from Roshydromet network across Russia
• Geometry of the catchment for correspond observation station point
• Daily hydrological values
  • Water level
    • In relative representation (sm)
    • In meters of Baltic system (m)
  • Water discharge
    • as an observed value (qms/s)
    • as a layer (mm/day)
• Daily meteorological values
  • Maximum and minimum daily temperatures (°C) from ERA5 and ERA5-Land
  • Total precipitation (mm/day) from ERA5, ERA5-Land, IMERG v06, GPCP v3.2 and MSWEP
  • Different kind of evaporation (mm/day) corresponded to each variable calculated in GLEAM model
• Set of hydro-environmental characteristics derived from HydroATLAS database

Each variable derived from the grid data was calculated for each watershed, taking into account the intersection weights of the watershed contour geometry and grid cells.

Coordinates of hydrological stations were obtained from resource of Federal Agency for Water Resources of Russia Federation—AIS GMVO

To calculate the contours of the catchment areas, a script was developed that builds the contours in accordance with the rasters of flow directions from MERIT Hydro. To assess the quality of the contour construction, the obtained value of the catchment area was compared with the archival value from the corresponded table from AIS GMVO. The average error in determining the area for 2080 catchments is approximately 2%

To derive values for different hydro-environmental values from HydroATLAS were developed approach which calculate aggregated values for catchment, leaning on type of variable: qualitative (Land cover classes, Lithological classes etc.) Or quantitive (Air temperature, Snow cover extent etc.). Every quantitive variable were calculated as mode value for intersected sub-basins and target catchment, e.g. most popular attribute from sub-basins will describe whole catchment which are they relating. Quantitative values were calculated as mean value of attribute from each sub-basin. More detail could be found in publication.

Files are distributed as follows:

Each file has some connection with the unique identifier of the hydrological observation post. Files in netcdf format (hydrological and meteorological series) are named in response to identifier.

Every file which describe geometry (point, polygon, static attributes) has and column named gauge_id with same correspondence.

• attributes/static_data.csv – results from HydroATLAS aggregation
• geometry/russia_gauges.gpkg – coordinates of hydrological observation stations

  • 	gauge_id	name_ru	name_en	geometry
    0	49001	р. Ковда – пос. Софпорог	r.Kovda - pos. Sofporog	POINT (31.41892 65.79876)
    1	49014	р. Корпи-Йоки – пос. Пяозерский	r.Korpi-Joki - pos. Pjaozerskij	POINT (31.05794 65.77917)
    2	49017	р. Тумча – пос. Алакуртти	r.Tumcha - pos. Alakurtti	POINT (30.33082 66.95957)

• geometry/russia_ws.gpkg – catchments polygon for each hydrological observation stations

  • 	gauge_id	name_ru	name_en	new_area	ais_dif	geometry
    0	9002	р. Енисей – г. Кызыл	r.Enisej - g.Kyzyl	115263.989	0.230	POLYGON ((96.87792 53.72792, 96.87792 53.72708...
    1	9022	р. Енисей – пос. Никитино	r.Enisej - pos. Nikitino	184499.118	1.373	POLYGON ((96.87792 53.72708, 96.88042 53.72708...
    2	9053	р. Енисей – пос. Базаиха	r.Enisej - pos.Bazaiha	302690.417	0.897	POLYGON ((92.38292 56.11042, 92.38292 56.10958...

  • Column ais_diff is corresponded to % error in area definition
• nc_all_q/
  • netcdf files for hydrological observation stations which has no missing values on discharge for 2008-2020 period
• nc_all_h
  • netcdf files for hydrological observation stations which has no missing values on level for 2008-2020 period
• nc_concat
  • data for all available geometry provided in dataset

More details on processing scripts which were used for development of this database can be found in folder of GitHub repository where I store results for my PhD dissertation

The size of the Russia Kitchen Appliances Market market was valued at USD 6.80 Million in 2023 and is projected to reach USD 9.81 Million by 2032, with an expected CAGR of 5.38% during the forecast period. Recent developments include: March 2023: Samsung's electronics new home appliances introduced Samsung’s 2023 Bespoke products will expand to 27 models. Can be wirelessly connected. Fifteen of them boast AI-enabled functions to cater to the users’ demands., July 2022: In the process of pulling up its stake in Russia, Whirlpool is planning to sell its Russian operations to Turkish conglomerate Arcelik, which is the parent company of the Beko and Blomberg appliance brands, for a sum of USD 231 million. The sales include all Whirlpool Russian resources., March 2022: LG Electronics suspended all its shipments to Russia. LG exists as a major force in the electronics industry, producing TVs, refrigerators, microwaves, dishwashers, and other kitchen appliances as well.. Key drivers for this market are: Expanding Construction and Real Estate Sector. Potential restraints include: Rising competition among the players. Notable trends are: Solid Demand Growth For Small Cooking Appliances.

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Russia RU: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Services data was reported at 902.574 USD bn in 2017. This records an increase from the previous number of 883.911 USD bn for 2016. Russia RU: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Services data is updated yearly, averaging 636.839 USD bn from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 911.603 USD bn in 2014 and a record low of 417.541 USD bn in 1998. Russia RU: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Gross Domestic Product: Real. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3 or 4. Data are in constant 2010 U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total;