Agriculture Reinsurance Market Size, Share & Trends Analysis Report by Product (Managed Crop Hail Insurance, Livestock Insurance, Bloodstock Insurance, Multi-Peril Crop Insurance, and Forestry Insurance), Region And Segment Forecasts, 2023-2031

Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Agriculture Reinsurance Market Snapshot

Chapter 4. Global Agriculture Reinsurance Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. COVID-19 Impact Analysis

Chapter 5. Market Segmentation 1: By Product Estimates & Trend Analysis
5.1. By Product & Market Share, 2019-2031
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2022 to 2031 for the following By Product:

5.2.1. Managed Crop Hail Insurance
5.2.2. Multi-Peril Crop Insurance
5.2.3. Livestock Insurance
5.2.4. Greenhouse Insurance
5.2.5. Aquaculture Insurance
5.2.6. Bloodstock Insurance
5.2.7. Forestry Insurance

Chapter 6. Agriculture Reinsurance Market Segmentation 2: Regional Estimates & Trend Analysis

6.1. North America

6.1.1. North America Agriculture Reinsurance Market revenue (US$ Million) estimates and forecasts By Product, 2023-2031
6.1.2. North America Agriculture Reinsurance Market revenue (US$ Million) estimates and forecasts by country, 2023-2031

6.1.2.1. U.S.
6.1.2.2. Canada

6.2. Europe

6.2.1. Europe Agriculture Reinsurance Market revenue (US$ Million) by Product, 2023-2031
6.2.2. Europe Agriculture Reinsurance Market revenue (US$ Million) by country, 2023-2031

6.2.2.1. Germany
6.2.2.2. Poland
6.2.2.3. France
6.2.2.4. Italy
6.2.3. Spain
6.2.3.1. UK
6.2.3.2. Rest of Europe

6.3. Asia Pacific

6.3.1. Asia Pacific Agriculture Reinsurance Market revenue (US$ Million) by Product, 2023-2031
6.3.2. Asia Pacific Agriculture Reinsurance Market revenue (US$ Million) by country, 2023-2031

6.3.2.1. China
6.3.2.2. India
6.3.2.3. Japan
6.3.2.4. Australia
6.3.2.5. Rest of Asia Pacific

6.4. Latin America

6.4.1. Latin America Agriculture Reinsurance Market revenue (US$ Million) by Product, 2023-2031
6.4.2. Latin America Agriculture Reinsurance Market revenue (US$ Million) by country, (US$ Million) 2023-2031

6.4.2.1. Brazil
6.4.2.2. Rest of Latin America

6.5. Middle East & Africa

6.5.1. Middle East & Africa Agriculture Reinsurance Market revenue (US$ Million) by Product, (US$ Million)
6.5.2. Middle East & Africa Agriculture Reinsurance Market revenue (US$ Million) by country, (US$ Million) 2023-2031

6.5.2.1. South Africa
6.5.2.2. GCC Countries
6.5.2.3. Rest of MEA

Chapter 7. Competitive Landscape

7.1. Major Mergers and Acquisitions/Strategic Alliances

7.2. Company Profiles

7.2.1. Munich Re
7.2.2. Swiss Re
7.2.3. Hannover Re
7.2.4. PartnerRe
7.2.5. SCOR Re
7.2.6. Everest Re
7.2.7. Polish Re
7.2.8. Hamilton Re
7.2.9. Sompo International
7.2.10. Toa Re.

Segmentation of Agriculture Reinsurance Market-

By Product-

• Managed Crop Hail Insurance
• Multi-Peril Crop Insurance
• Livestock Insurance
• Greenhouse Insurance
• Aquaculture Insurance
• Bloodstock Insurance
• Forestry Insurance

By Region-

North America-

• The US
• Canada
• Mexico

Europe-

• Germany
• The UK
• France
• Italy
• Spain
• Rest of Europe

Asia-Pacific-

• China
• Japan
• India
• South Korea
• South East Asia
• Rest of Asia Pacific

Latin America-

• Brazil
• Argentina
• Rest of Latin America

 Middle East & Africa-

• GCC Countries
• South Africa
• Rest of the Middle East and Africa

 InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

• Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
• External and internal proprietary databases, regulatory databases, and relevant patent analysis
• Statistical databases, National government documents, and market reports
• Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

• Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
• Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
• Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
• End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.