【当該年度の実績概要】交付申請書に記載の研究目的および研究実施計画に沿って、２０２３年度に以下のことを実施した。 １．２０２２年度に調査取得した、個人の金融商品購買選好に関する調査データ（有効回答１０００件）を精査し、三種のリスク区分ごとにリスク・プレミアムの算定を行った。これらに基づき、各区分のリスク選好についての仮説（純粋リスクには強い回避選好、狭義の投機的リスクには穏やかな回避選好、射幸リスクには強い愛好選好を想定）を、期待値原理に基づくリスク定量化によって検証し、これらの妥当性を確認した。 ２．同じデータに基づき、純粋リスクにおけるリスク回避選考の強さと、投機的リスクにおけるリスク愛好選好の強さの相関を分析した。これらのリスクを定量化して回帰分析を行ったところ、得られた相関はごく小さかった。これらは負の相関があると考えるべき理由があるように思えたため、これに反する結果が得られたことの意味について考察を行っているが、先行研究が少ないこともあり、年度内には理由を理論づけるに至っていない。 ３．上記２．の結果が真のリスク性向を表すものであれば、興味深い結果と考えられる。これを確認するため、調査票設計上の問題に起因するバイアスでないかを精査しており、第二回、第三回調査の実施が遅延している。 ４．この状況を踏まえ、研究期間を一年延長し、第二回以降の調査の実施及び成果の論文化は、２０２４年度に延期する。（補助事業期間延長申請済み）
【２０２４年度の計画】１．調査票のバイアス検証および第二回・第三回調査を実施する。 ２．3区分ごとの市場のリスク・プレミアムの推定結果を学会誌に公表する。 ３．純粋リスクにおけるリスク回避選考と投機的リスクにおけるリスク愛好選好の相関（無相関に近いと想定）について、その計量結果と原因の分析を実施する。

伝統的保険学は、大数の法則を基礎とした保険を対象としてきた。一方、自然災害など集積性の高い損害をもたらすリスク、サイバー攻撃など時間による変化の大きいリスク、海上保険など同種の対象物が少数であるリスクなど、大数の法則の適合性が低い「非マスリスク」に対する保険の重要性は増している。非マスリスク保険の保険料算定に関する思想と数理的な技法を研究し、併せて国際的な比較を試みることで、原則の確立を目指している。本年度は、米国における非マスリスクへの重要な対応手段であるNon-admitted Insuranceについての調査結果を取りまとめ、他の諸国の監督制度と合わせて、金融庁ディスカッションペーパー「保険契約者のニーズを踏まえた保険商品開発に係る規制の在り方」を著し、2025年8月に発表した（本学商学学術院中出哲教授との共著。英語版は2026年3月）。この中で、リスクの性質（マスリスクと非マスリスク）および契約者の性質（個人と企業）に応じて、審査制度をさらに分化させることなどを提言した。また、自動運転社会において、自動車保険が非マスルスク化する可能性と、その影響をまとめ、公益財団法人 自動車製造物責任相談センター　年次報告書　巻頭論文「技術の高度化に伴う自動車製造物責任の変容と非マスリスク化への対応」を執筆した。

This study introduces a novel framework that consistently explains people's risk preferences. The author aims to evaluate these preferences using this innovative framework quantitatively.The framework categorizes risk into three types: pure, speculative, and speculative (or lottery). This explains the seemingly contradictory mix of risk-averse preferences for insurance and risk-loving preferences for lotteries. This comprehensive approach will allow us to measure the risk premium for each of the three categories, providing novel insights into risk management strategies.This study categorizes risk into three types: pure risk (insurance), speculative risk (stock investments), and lottery risk (gambling) to capture varying risk preferences. Using survey data from 1,000 Japanese participants, the study assesses willingness to pay (WTP) for insurance, stock investments, and lotteries. The research introduces two metrics to quantify risk appetite: a risk premium coefficient (h) and risk premium per unit of standard deviation (RP/Δσ). The research plan involves conducting multiple surveys over three years. The survey was conducted in fiscal year 2022, yielding 1,000 valid responses. Significant findings include that individuals exhibit domain-specific risk preferences, with risk aversion predominant in insurance, risk-seeking behavior in lotteries, and moderate risk aversion in stock investments. Importantly, risk preferences across categories show minimal correlation. Risk attitudes are not universal; being enthusiastic about insurance does not imply that individuals are risk-averse regarding investments or gambling. Individuals demonstrate varying risk behaviors based on the nature of the risk. These findings suggest that economic models should consider context-dependent risk preferences rather than fixed personal ones. The results impact financial decision-making, insurance pricing, investment behavior, and the design of policies. As of the end of March 2025, the results and implications have been incorporated into a paper titled “Understanding Risk Preferences: A Three-Type Classification Approach.” This paper was accepted for the upcoming 2025 World Risk and Insurance Economics Congress in Calgary, August 3-7, an international conference co-hosted by the American Risk and Insurance Association (ARIA), the European Group of Risk and Insurance Economists (EGRIE), and the Asia-Pacific Risk and Insurance Association (APRIA). We aim to publish the results in The Journal of Risk and Insurance after getting feedback at the WRIEC 2025. Additionally, we believe these findings suggest further insights when the issue is explored in more detail, and we are currently developing the design of subsequent surveys to gain a broader understanding.

This study introduces a novel framework that consistently explains people's risk preferences. We aim to evaluate these preferences using this innovative framework quantitatively.The framework divides risk into three categories: pure, speculative, and shooting (lottery). This explains the seemingly contradictory mix of risk-averse preferences for insurance and risk-loving preferences for lotteries. This comprehensive approach will allow us to measure the risk premium for each of the three categories, providing valuable insights for risk management strategies.Our research plan entails conducting multiple surveys over a three-year period (initially over two years). The survey was conducted in FY2022, with 1,000 valid responses. As of the end of March 2024, we analyzed the survey data and measured the risk premium regarding expected value and variance pricing. We identified the distribution of subjects' risk premiums. We also conducted cross-sectional analyses and regression analyses between risk preferences for different types of risks. It showed that the magnitude of risk aversion in pure risk has almost no relation with the magnitude of risk love in shooting risk. We believe these findings are worth further exploration and are currently working on the design of subsequent surveys to further clarify the meanings of the findings.We aim to publish the results in foreign or domestic journals in FY 2024.

This study proposes a framework to explainpeople's risk preferences in a consistent manner and aims to quantitativelyevaluate risk preferences using this framework. The framework divides risk into threecategories: pure risk, speculative risk, and lottery risk. This explains theseemingly contradictory mix of risk-averse preferences for insurance andrisk-loving preferences for lotteries. The research plan is to conduct multiplesurveys over a two-year period and to measure the risk premium for each of thethree categories. This year's objectives were (1) to examinethe design of the survey, particularly the ease of understanding the survey questions by respondents,(2) to verify the validity of the method by conducting the first round of the survey,and (3) to obtain 1,000 valid responses.As of the end of March, (1) to (3) above progressedas expected. In FY2023, we plan to analyze the dataobtained from the first survey and measure the risk premium, design and conductthe second and subsequent surveys, analyze the data, and publish the results inforeign or domestic journals.