OECD Insurance Statistics, 1983-2014
Bibliographic record
Abstract
The <i>Organisation for Economic Co-operation and Development (OECD) Insurance Statistics</i> are presented in the following tables:<br> <br> <b>Balance sheet and income</b><br> The balance sheet and income dataset shows data for direct insurance and reinsurance by life, non-life and composite categories shown in US dollars or national currency. Data are available from 2008 to 2010. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>Business written in the reporting country</b><br> This dataset contains business written in the reporting country on a gross and net premium basis. It contains a breakdown by ownership between domestic companies, foreign-controlled companies and branches and agencies or foreign companies. It also comprises various type of premiums (gross premiums, premiums ceded, net written premium) as well as insurance type (life, non-life, composite) and facultative reinsurance may be included under (direct business or reinsurance accepted) according to practice in the reporting country. Data are expressed in national currency, USD or Euro (in millions) and presented from 1983 onwards. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States, Hong Kong, India, Malaysia, Russian Federation, Singapore, South Africa and Thailand.<br> <br> <b>Commissions</b><br> This dataset includes statistics related to commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies. The commissions in the reporting country can then be compared by ownership (domestic undertakings, foreign controlled undertakings, branches and agencies of foreign undertakings) by insurance type (life, non-life, composite) and facultative reinsurance (direct business, reinsurance accepted). Data are expressed in national currency, USD or Euro (in millions) and presented from 1993 onwards. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>Gross claims payments</b><br> This dataset contains data related to gross claims payments in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies. The core variable can be further analysed by type of insurance (life, non-life, composite). Data are expressed in different currencies and starting from 1993. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>Gross operating expenses</b><br> This dataset contains gross operating expenses in the reporting country, with a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies. This table also compares the core variable by type of insurance (life, non-life, composite) and currency (euro, USD). Data are available starting from 1993. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>Insurance activity indicators</b><br> This comparative table comprises statistics on the insurance industry indicators as this sector is a key component of the economy by virtue of the amount of premiums it collects, the scale of its investment and the essential social and economic role it plays on personal and business risk coverage. This dataset includes insurance activity indicators such as market share, density, penetration, life insurance share, premiums per employee, retention ratio, ratio of reinsurance accepted, market share of foreign companies and market share of branches/agencies. Data are presented from 1983 onwards with annual datapoints. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States, Hong Kong, India, Malaysia, Russian Federation, Singapore, South Africa and Thailand.<br> <br> <b>Insurance business by domestic and foreign risks</b><br> This subset of OECD Insurance Statistics presents statistics on the insurance industry with a focus on domestic and foreign business risk. The type of risk can be further analysed by type of premium (net written premium, gross premiums, premium ceded), ownership (domestic company, foreign controlled undertakings, branches and agencies of foreign undertakings) and type of insurance (life, non-life, composite). Data are expressed in different currency terms and are presented from 1983 onwards. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>Insurance business written abroad by branches</b><br> This dataset includes statistics pertaining to the insurance business written abroad by branches. It also includes variables such as premium type (gross premium, premium ceded, net written premium), branches and agencies, subsidiaries, insurance type (life, non-life, composite), partner country, direct business and reinsurance accepted. Data are available in Euro/ USD currency and are presented from 1983 onwards. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States.<br> <br> <b>Insurance business written in the reporting country</b><br> This dataset includes statistics on business written in the reporting country by premiums (gross premium, premium ceded, net written premium), by classes of non-life insurance (freight insurance, general liability insurance, treaty reinsurance). Business should include all business written in the reporting country, whether in respect of domestic or foreign (worldwide) risks. Data are presented from 1987 onwards. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States.<br> <br> <b>General Insurance Statistics </b><br> This dataset provides information on number of insurance companies and employees within the sector. The number of insurance undertakings is then examined by ownership (domestic undertakings, foreign controlled undertakings, branches and agencies of foreign undertakings) and by insurance type (life, non-life, composite, reinsurance). Number of insurance employees is also available by employer type (insurance undertakings, intermediaries). Data is available starting from 1983. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States, Hong Kong, India, Malaysia, Russian Federation, Singapore, South Africa and Thailand.<br> <br> <b>Destinations of investments by direct insurance or reinsurance companies</b><br> This dataset includes statistics related to outstanding investment by direct insurance companies, classified by investment category (real estate, mortgage loans, shares, bonds, loans, other investment), companies nationality, destination (foreign or domestic), ownership, insurance type, insurer type (direct insurer, reinsurer). Data are expressed in different currencies and are available from 1988 onwards. The countries
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.069 | 0.050 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".