accommodation or obfuscation? product innovation in the ... · xiaochen jing & daniel bauer...

Accommodation or Obfuscation? Product

Innovation in the Variable Annuities Market

Xiaochen Jing and Daniel Bauer

University of Wisconsin - Madison

April 29th, 2020

/ 22 Background and Literature

• Separate account life insurance contracts linked to a list of financialinstruments with tax advantage

• 2 trillion USD in net assets (25% of US insurance industry’s total assets)

• Equipped with optional features

I Guaranteed Living Benefits (GLBs)

I Guaranteed Minimum Death Benefits (GMDBs)

• 75% of all new VAs include GLBs

• Withdrawal guarantees most popular living benefits since mid-2000s

I Guaranteed Minimum Withdrawal Benefits (GMWBs)

I Guaranteed Lifetime Withdrawal Benefits (GLWBs)

Xiaochen Jing & Daniel Bauer Product Innovation in the Variable Annuities Market


• Plenty of product variation in the VA marketI Radical: GMDB, GMAB, GMIB, GMWB, GLWBI Incremental: Surrender Charge Schedule, Free Withdrawals, Step-Up

Provisions, Impact of Withdrawals, etc.I Beneficial to consumers with specific needs

• VAs are complex productsI Multi-dimensional payoff functionsI On-going decision making throughout the contract periodI Consumers may not be sophisticated to choose optimally



• Classic View on Product Innovation

I Market Incompleteness(Allen and Gale, 1994; Duffie and Rahi, 1995)

I Market Frictions(Ellul et al., 2018; Koijen and Yogo, 2020; Moenig and Bauer, 2016)

• Potential “dark side” of Product Innovation: ObfuscationI Strategic pricing of complexity

(Gabaix and Laibson, 2006; Carlin, 2009)

I Empirical Studies from Retail Financial Markets(Henderson and Pearson, 2011; Célérier and Vallée, 2017)


/ 22 Outline

• This paper: what drives product innovation in the Variable Annuitiesmarket?

• A stylized model on product price and complexity

• Empirical findingsI In general, product price is positively associated with complexityI Earlier innovations have high pricesI Recurring pattern of radical and incremental innovation


/ 22 Table of Contents

1 Background and Literature

2 Outline

3 Model

4 Data and Summary Statistics

5 Regression Analysis

6 Conclusion


/ 22 ModelAn Extension to Carlin (2009)

• N + 1 homogeneous firms: profit maximizersI Choose effort ej for product innovationI Choose product price and complexity (pj , kj)

• Unit mass of consumersI Sophisticated and unsophisticated consumers

? The proportion depends on product complexity in the market

I Type I and type II consumers

Utility Current InnovationType I 1 0Type II 0 1


/ 22 ModelTwo-stage Game

• Stage one:I Firms choose levels of effort for innovationI Lottery-like probability of success Pj =

ej∑i ei

• Stage two:I Successful innovator is revealedI Firms choose price and complexity (pj , kj) for their productsI Consumers choose one product to purchase

• Equilibrium solved in reverseI In stage two, successful innovator chooses product typeI In stage two, unsuccessful innovators compete in a Carlin’s gameI In stage one, all firms compete in a Tullock’s game


/ 22 ModelTwo-stage Game

Proposition 1

Successful innovator chooses monopolistic price, lowest complexity,and attracts all type II sophisticated consumers in equilibrium.

Proposition 2

Unsuccessful innovators compete over type I sophisticated consumers.Higher competition leads to higher levels of complexity.


/ 22 Data and Summary Statistics

• VA prospectus: typically several hundred-page long documents withdetailed description

• Our source: Morningstar Annuity IntelligenceI 2,302 plain VA contracts and 22,623 VA + benefit combinationsI Staring from 1994I Numerical values on fees and benefitsI Textual description on add-ons and conditions



• Frequent innovation and increasing complexity



• Increasing VA fees and benefit charges

• In line with recent findings


/ 22 Data and Summary StatisticsAnalysis at the benefit level

• Popularity of various optional benefits overtime



• Sub-markets characteristics



• Complexity trends in sub-markets



• Price trends in sub-markets

• Aggregate vs. sub-markets, virtuous and obfuscating innovations


/ 22 Regression AnalysisProduct Complexity

• Measured by description length and number of scenarios

• Baseline model

Complexityi = α∗Firsti+βyear ∗Yeari+βtype∗Benefit Typei+Fixed Effectsi+εi

• Interaction term to capture sub-market patterns

Complexityi =α ∗ Firsti + βyear ∗ Yeari + βtype ∗ Benefit Typei

+ γ ∗ Yeari ∗ Benefit Typei + Fixed Effectsi + εi



• Pair of terms to capture the “increasing-stagnating" trendI t0i : time after first sub-market innovationI txi = max(t0i − x , 0)

Complexityi =α ∗ Firsti + βyear ∗ Yeari + βtype ∗ Benefit Typei

+ γ0 ∗ t0i + γx ∗ txi + Fixed Effectsi + εi




Sean

矩形

/ 22 Regression AnalysisVariable Annuity and Benefit Fees

• Measured by total fees of the product

• Baseline model

Feei =α ∗ Firsti + βyear ∗ Yeari + βtype ∗ Benefit Typei + βcomp ∗ Complexityi

+ Fixed Effectsi + εi

• Interaction term to capture sub-market patterns

Feei =α ∗ Firsti + βyear ∗ Yeari + βtype ∗ Benefit Typei + βcomp ∗ Complexityi

+ γ ∗ Yeari ∗ Benefit Typei + Fixed Effectsi + εi


/ 22 Regression AnalysisVariable Annuity and Benefit Fees


Sean

矩形

/ 22 Conclusion

• Extended Carlin’s model for product complexity by allowing for "virtuous"product innovationI In equilibrium, "virtuous" and "obfuscating" firm behavior co-exist.

• Empirical analysis on Variable Annuity marketI In general, product price is positively associated with complexityI Earlier innovations have high pricesI The recurring pattern of radical and incremental innovation


/ 22

Thank you!


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