Мировой Атлас Данных

Insurance industry mergers and acquisitions (M&A) report highlights the current state of insurance industry M&A, examines key drivers and trends for 2016, and suggests what leading insurance organizations should be doing to identify and capitalize on M&A opportunities as they move forward.Insurance was one of many industries that enthusiastically embraced M&A in 2015 as a way to boost revenue growth, enter new markets, and improve operating efficiency.  The report assists insurance industry leaders with their M&A planning and implementation as well as suggest them to plan for and address six marketplace drivers and trends that may help or hinder their M&A plans: An environment of high confidence: Despite generally positive market conditions entering 2016, there always exist potential cross-currents and areas of uncertainty that might impede inbound and outbound M&A. In the US, insurance executives should be mindful of potential impacts from fluctuating economic conditions, volatility in the US equity markets, rising interest rates, and the 2016 presidential election.Regulatory developments cut both ways: The trend of more stringent regulation continues and insurance companies should take note of several regulatory developments that may impact their 2016 M&A planning. These include capital requirements, the DOL and CFPB rule package on retirement asset management, inversion regulations, and proposed PFIC regulations on hedge funds. A reasonable valuation environment leading to an increased supply of acquisition targets: A major impediment to more M&A activity has been a scarcity of available targets. This supply/demand imbalance may improve in 2016, thanks, in part, to a reasonable valuation environment.Continued demand by foreign buyers to invest in the US market: Foreign companies, especially those from China and Japan, see US insurance assets as valuable additions to their portfolios and are buying business-building platforms to enable future growth and expansion.The increase in number and strategic significance of fintech-oriented transactions: Start-up financial technology ("fintech") organizations offer significant potential for insurers as venture portfolio investments, components of a broader economic ecosystem, or potential acquisitions that become integrated into existing operations.Investment activity by "alternative capital": Private equity firms, hedge funds, and other sources of alternative capital will continue to shop for insurance properties in 2016; however, the industry's lower and/or longer-run rates of return may leave the window open for capital-rich strategic buyers that can offer a better price and create synergies that trump financial buyers.

Current Payers: Data Vintage: COAPCDQ42013 This Data Vintage stamp reflects indicates which payer data is included in this report, along with any special conditions and data submission waivers associated with the payer data. Current payers include the 12 largest commercial payers in Colorado (large-group and individual fully insured lines of business) and Medicaid. Small group, self-insured commercial payers and Medicare is not included. Please visit the Glossary in the Resources tab at http://www.cohealthdata.org for the full Data Vintage information, and visit the Current Data/Future Milestones link on the Resources tab to see the timeline for adding additional payers to the database. Data Completeness Score The data completeness score is an indicator of how comprehensive the coverage of lives in the database reflects the population. It is represented as a Quartile score of C1-C4 with C1 being the lowest score. The lower the score, the greater the degree of caution should be used in interpreting the results. - C1 indicates that 25% of the population or less are included in the data. - C2 represents that between 25% and 50% of the population are included in the data. - C3 represents that between 50% and 75% of the population are included in the data. - C4, the upper range, represents at least 75% of the population are included in the data. Completeness scores are approximate estimations based on data sources internal and external to the APCD. They are designed to provide an appropriate level of caution to users of the APCD. It’s important to keep in mind that caution needs to be exercised when reviewing data from C1 and C2 and that data becomes more reliable as you move from C3 to C4. 3M Technology "3M™ Health Information Systems provides grouping technology used in the creation of the data in this report. 3M™ APR-DRG Software (All Patient Refined Diagnoses Related Groups) is a classification system to categorize hospital stays based on diagnoses and procedures performed. 3M™ Clinical Risk Grouping Software (CRGs) categorize a population based on health status and use of health care services from claims submitted over a calendar year. 3M™ EAPG Software (Enhanced Ambulatory Patient Groups) is a patient classification system designed to explain the amount and type of resources used in an ambulatory visit. 3M™ Potentially Preventable Readmissions Software (PPR) identifies those admissions in an acute care setting that have subsequent readmissions, within 30 days that are both clinically related and are deemed potentially preventable. Please reference the following link for more information on 3M Health Information Systems grouping technology: http://solutions.3m.com/wps/portal/3M/en_US/Health-Information-Systems/HIS/Products-and-Services/Classification-and-Grouping/" Illness Burden The Illness Burden for a population is a number used to measure the relative health of that group based upon the number and types of healthcare services used. A higher number (above the 1.0 average) indicates that the population uses more and/or costlier services relative to the rest of the population in the database and is often a result of a higher number of people with chronic diseases like diabetes or asthma. Likewise, smaller numbers (below the 1.0 average), indicate a relatively healthier population using less health care services. Compared to Expected Compared to Expected (C2E) values indicate how different the actual observed data in an area is from an expected value (an average based upon the type of people that live in that area). The C2E is always represented as a percentage. Numbers in red represent those “compared to expected” values that are in excess of 25%, indicating a higher than average expected cost or use of services. Likewise, numbers in green represent those “compared to expected” values that are below -25% indicating a lower than average expected cost or use of services. BETOS Categories BETOS is an acronym for Berenson-Eggers Type of Service. BETOS Categories are groupings of professional services based on the HCPCS (Health Care Procedure Coding System, including CPT codes) used by the provider to identify the services rendered at the time of service. Please see the following link for additional information: http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareFeeforSvcPartsAB/Downloads/BETOSDescCodes.pdf CPT Codes CPT is an acronym for Current Procedural Terminology and is a registered trademark of the American Medical Association. For more information on CPT codes, please refer to the following location: http://www.ama-assn.org/ama/pub/physician-resources/solutions-managing-your-practice/coding-billing-insurance/cpt/about-cpt.page Terms & Conditions of Use This report and any data made available on or obtained through the APCD website is subject to our current Terms of Use and Privacy Policy available at: http://www.cohealthdata.org. Data Note Data (particularly rates and percentages) from Colorado counties with fewer than 5,000 people are more volatile than data from counties with larger populations. Readers should exercise caution when interpreting results from counties with small populations. This includes: Baca, Cheyenne, Costilla, Custer, Dolores, Gilpin, Hinsdale, Jackson, Kiowa, Lincoln, Mineral, Ouray, Phillips, San Juan, Sedgwick, Saguache, and Washington counties.

Since the collection of 2009 data, the scope of the OECD Global Insurance Statistics questionnaire has been expanded. These changes led to the collection of key balance sheet and income statement items for direct insurance and reinsurance sectors, such as: gross claims paid, outstanding claims provision (changes), gross operating expenses, commissions, total assets, gross technical provisions (of which: unit-linked), shareholder equity, net income.

Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Business written in the reporting country on a gross and net premium basis. It contains a breakdown between domestic companies, foreign-controlled companies and branches and agencies or foreign companies.

Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agences of foreign companies.

Corporate Statistics of Insurance Companies, 2015

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business datawhere composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Click to collapse Item coverage Outstanding investment by direct insurance companies, classified by investment category, by the companies' nationality and by its destination (domestic or foreign). As of 2009, investment data exclude assets linked to unit-linked products sold to policyholders.

This report provides countrywide and state-specific premium and exposure information for noncommercial dwelling fire insurance and for homeowners insurance package policies. Homeowners package policy data are for the homeowners owner-occupied policy forms (HO-1, HO-2, HO-3, HO-5 and HO-8), the tenant policy (HO-4) and the condominium/cooperative unit owner’s policy (HO-6). This narrative describes the data and discusses the way economic, demographic and natural phenomena impact the price of homeowners insurance.Data consist of written exposures, expressed as house-years,1 and aggregate written premiums by state and countrywide for the 2013 data year. Premium and exposure information was collected for all states and the District of Columbia. The data are displayed in five tables. Three tables show individual state and countrywide exposures grouped by 1) policy type; 2) individual policy form; and 3) amount of insurance coverage, divided into ranges, with percentages of total exposures provided. The last two tables display by-state and countrywide average premiums. Average premiums are calculated by dividing premiums by exposures for each policy form and range of insurance coverage, and represent the cost of a year of coverage. Percentages of totals are provided.Policy forms included in the report are described in detail in the following section. The ranges of insurance amounts extend to higher levels of coverage for the dwelling fire and homeowners owner-occupied policy forms than those for the tenant and condominium insurance, because premiums for the latter two policy forms do not include coverage for the residential structure.To the extent that data are reported to statistical agents, data for statutorily established FAIR plans are included.

Insurance Europe is the European insurance and reinsurance federation. Through its 34 member bodies - the national insurance associations - Insurance Europe represents all types of insurance and reinsurance undertakings, eg pan-European companies, monoliners, mutuals and SMEs. Insurance Europe, which is based in Brussels, represents undertakings that account for around 95% of total European premium income. Insurance makes a major contribution to Europe’s economic growth and development. European insurers generate premium income of more than €1 100bn, employ almost one million people and invest almost €8 400bn in the economy.

Federal Supplementary Medical Insurance Trust Fund - Prescription Drug Account (75X80041): Income Statement - Unaudited, March 2017

The FAS is the sole source of global supply-side data on financial inclusion, encompassing internationally-comparable basic indicators of financial access and usage. From 2014, FAS also includes indicators for mobile money. In addition to providing policy makers and researchers with annual geographic and demographic data on access to basic consumer financial services worldwide, the FAS is the data source for the G-20 Basic Set of Financial Inclusion Indicators endorsed by the G-20 at the Los Cabos Summit in 2012.  The FAS database currently contains 152 time series and 47 key indicators which are grouped into two dimensions: (i) geographic outreach of financial services; and (ii) use of financial services. The database includes annual data from 2004 and metadata for the reporting jurisdictions.

This part contains general information on number of insurance companies and employees within the sector.

Insurance companies' key figures: Germany, years, economic activities

Global Financial Stability Report (GFSR) finds that six years after the start of the crisis, the global economic recovery continues to rely heavily on accommodative monetary policies in advanced economies. Monetary accommodation remains critical in supporting the economy by encouraging economic risk taking in the form of increased real spending by households and greater willingness to invest and hire by businesses. However, prolonged monetary ease may also encourage excessive financial risk taking.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Gross claims payments in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. This part contains gross operating expenses in the reporting country, with a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.

The new database on Institutional investors' assets replaces the former database on Institutional Investors. It constitutes an attempt to better integrate these data in the framework of the System of National Accounts (SNA). Institutional Investors' assets are mainly compiled on the basis of the System of National Accounts (SNA93).

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Breakdown of net premiums written in the reporting country in terms of domestic risks and foreign risks, thus providing an indicator of direct cross-border operations of insurance business.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Covers business written abroad by branches, agencies and subsidiaries established abroad of domestic undertakings and includes all business written outside the country by these entities (in both OECD and non-OECD countries).

This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.

This report is the 28th in an annual series published by the NAIC. It contains key statistics on the resources and regulatory activities of the members of the NAIC, which include the 50 states, the District of Columbia, American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. The data presented in this report were obtained primarily through an extensive survey completed by each of the departments

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Annual Statement Information for Life/Health Insurance Companies in 2014

Enrollment is measured in life-years (which is member months divided by 12). Enrollment data approximate the number of people enrolled in comprehensive major medical insurance and mini-med plans. Plans that shared a parent company or insurer group were collapsed into one insurer for the purposes of this analysis. 

    MEPS employer-based health insurance data are produced in the year following data collection. Private-sector data are posted in July and government data are posted in November. MEPSnet/IC is based on aggregate statistics, thus not all possible queries can be addressed. If the query is not possible, MEPSnet/IC will not allow you to choose certain parameters.

Statistics in the insurance sector: total market, portfolio, number of institutions, home equity institutions, institutions operations, among others. Frequency: Annual, available last year

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Publication: Annual Statement Information for Property/Casualty Insurance Companies in 2014

Publication: Annual Statement Information for Property/Casualty Insurance Companies in 2014

Publication: Annual Statement Information for Property/Casualty Insurance Industry Companies in 2014

Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions.

Uganda Insurance Statistics covers Number of Non-Life Insurance Policies, Number of Life Insurance Policies, Life Insurance Premium Incomings, Life Insurance Reinsurance Outgoings, Life Insurance Net Premium Income, Non-Life Insurance Premium Incomings, Non-Life Insurance Reinsurance Outgoings, Non-Life Insurance Net Premium Income, Non-life net Incurred Claims and Life net Incurred claims, by Class: Life . Source: Uganda Insurance Commission

United Kingdom : Insurance Corporations and Pension Funds, Balance Sheet Liabilities - Equity and Investment Fund Shares

The ASEC asks respondents about their health insurance coverage throughout the previous calendar year. Respondents may report having more than one type of coverage. In this analysis, individuals are sorted into only one category of insurance coverage using the following hierarchy: Medicaid: Includes those covered by Medicaid, the Children’s Health Insurance Program (CHIP), and those who have both Medicaid and another type of coverage, such as dual eligibles who are also covered by Medicare. Employer: Includes those covered by employer-sponsored coverage either through their own job or as a dependent in the same household. Other Public: Includes those covered under the military or Veterans Administration as well as nonelderly Medicare enrollees. Non-Group: Includes individuals and families that purchased or are covered as a dependent by non-group insurance. Uninsured: Includes those without health insurance and those who have coverage under the Indian Health Service only. For example, a person having Medicaid coverage in the first half of the year but employer-based coverage in the last months of the year would be categorized as having Medicaid coverage in this analysis. N/A: Estimates with relative standard errors greater than 30% are not provided.

The ASEC asks respondents about their health insurance coverage throughout the previous calendar year. Respondents may report having more than one type of coverage. In this analysis, individuals are sorted into only one category of insurance coverage using the following hierarchy: Medicaid: Includes those covered by Medicaid, the Children’s Health Insurance Program (CHIP), and those who have both Medicaid and another type of coverage, such as dual eligibles who are also covered by Medicare. Employer: Includes those covered by employer-sponsored coverage either through their own job or as a dependent in the same household. Other Public: Includes those covered under the military or Veterans Administration as well as nonelderly Medicare enrollees. Non-Group: Includes individuals and families that purchased or are covered as a dependent by non-group insurance. Uninsured: Includes those without health insurance and those who have coverage under the Indian Health Service only. For example, a person having Medicaid coverage in the first half of the year but employer-based coverage in the last months of the year would be categorized as having Medicaid coverage in this analysis. N/A: Estimates with relative standard errors greater than 30% are not provided.

The Herfindahl-Hirschman Index (HHI) is a measure of how evenly market share is distributed across insurers in the market. HHI values range from 0 to 10,000, with an HHI closer to zero indicating a more competitive market and closer to 10,000 indicating a less competitive market. An HHI index below 1,000 generally indicates a highly competitive market; an HHI between 1,000 and 1,500 indicates an unconcentrated market; a score between 1,500 and 2,500 indicates moderate concentration; and a value above 2,500 indicates a highly concentrated (uncompetitive) market. N/A: Data not available.