Does Regulation Matter? Riskiness and Procyclicality of Pension Asset Allocation - Marie Briere -...

Does Regulation Matter?

Riskiness and Procyclicality of Pension Asset AllocationL.N. Boon Amundi, Netspar, Paris Dauphine and Tilburg

University M. Brière Amundi, Paris Dauphine University and

Université Libre de BruxellesS. Rigot Université Paris Nord, CEPN

OECD–APG Workshop – April 2014Pension Funds Regulation and Long Term InvestmentPreliminary – Do not quote

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� Ongoing debate on pension regulation in Europe: application of a Solvency Framework (EIOPA, 2012) ?

� Our question: does the type of regulation have an influence on the asset allocation of DB pension funds?– % of risky assets– Procyclicality

� We attempt to quantify the importance of regulatory factors on top of individual/ structural characteristics

� US, Canada and the Netherlands are particularly interesting cases :– They underwent notable regulatory changes: Pension Protection Act in

2006 in the US, Financial Assessment Framework in 2007 in the Netherlands

– Fund regulation varies across countries and types of funds

Motivation

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Related Literature: Drivers of pension fund’s allocation

� Individual characteristics of the funds are a major determinant of the riskiness of pension plan’s asset allocation– Size (Dyck and Pomorski, 2011)– Maturity (Rauh, 2009 ; Bikker, 2011)– Inflation indexation (Sundaresan and Zapatero, 1997; Lucas and Zeldes,

2006)

� Institutional characteristics of the plan: presence of a guaranteeing mechanism (PBGC in the US, PBGF in Ontario)– This insurance is in effect a put option that reduces the negative impact of

pension liabilities on the firm’s value (Sharpe, 1976 ; Treynor, 1977; Nielson and Chan, 2007; Crossley and Jametti, 2013)

� Regulatory environment– US public funds increased their risky asset allocation to maintain high

discount rates and present lower liabilites (Pennachi and Rastad, 2011; Andonov et al. 2013)

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Related Literature: Debate on the efficiency of regulation

� Use of risk models to calibrate solvency buffers– Limit financial insitutions’ ability to take risk (Severinson and Yermo, 2012) – Generate procyclical investment (Bec and Gollier, 2009)– Generate substantial economic costs when repeated short term VaR

constraints are imposed on long term investors (Shi and Werker, 2012)

� Mark-to-market accounting methods– Constitute an additional source of price volatility, especially for long maturity

or illiquid assets (Plantin et al., 2008)– Limit investors’ ability to take risk (Severinson and Yermo, 2012) – Generate procyclical investment (Novoa, Scarlata and Solé, 2009)– Generate contagion (Allen and Carletti, 2008)

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� Empirical investigation of the drivers of pension fund’s asset allocations

– Expanding the literature over all regulatory dimensions– Quantifying / comparing the impact of regulation with other explanatory

factors

� Main Findings

– Regulatory factors play a strong role in explaining pension fund’s asset allocation choices

– They have a much larger economic impact than individual characteristics– Similar in amplitude to institutional factors

Our Paper

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� Regulatory changes induced a significant reduction in risky assetallocation

� Risk-based capital requirements have the strongest impact

– They induce a strong reduction in risky asset weights, especially equities– They have positive impact on alternatives (especially private equity, real

estate) and risky fixed income (mainly high yield)

� The choice of the liabilities discount rate comes as the second largest factor

Our Results: Riskiness of asset allocation

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� We build two original procyclicality measures

– Funds are procyclical in the sense that they do not fully rebalance

– Strong evidence of additional procyclicality during financial crises (asset weight decrease stronger than implied by asset drift)

� Little evidence of the impact of regulation on procyclicality

– Quantitative investment restrictions reduce procyclicality on the restrictedasset classes

– Counterintuitively, risk-based regulation induced a slighly lowerprocyclical behavior

– Result driven by the temporary regulatory slackening during the last crisis in the Netherlands

Our Results: Procyclicality

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Differences in Pension Funds’ Regulatory Environment

US public US private Canada public and privateDutch public and private

INVESTMENT RESTRICTIONS

Quantitative investment restrictions

YesNo unified regulation

None

Prior to 2005:Max 30% on foreign assets

2005-2010:Max 15% on resourceproperty, 25% real estate andCanadian natural resourceproperty.

After 2010:None

None

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US public US privateCanada public and

privateDutch publicand private

VALUATION REQUIREMENTS : ASSETS

Assetvaluation

GASB 27: Actuarial value

Before 2006: ERISA+FAS87Fair value, discounted cash flow, book value,smoothed value

After 2006: PPA +FAS157Fair value with 24M smoothing (smoothed value bounded between 90%-110% of asset’s current market value)

Before 2000: CICA3460 Market value or market related value.

After 2000: CICA3461Fair value or market related value adjusted to moderate its volatility,discounted cash flows,constant yield to maturity for illiquid assets.

After 2011: IAS19Market value

Before 2007: PSWMarket value

After 2005: IAS19Market value tocalculate the unfunded pension liabilities for listed corporate sponsors

After 2007: FTKMarket value

In red: funding regulation

In blue: accounting regulation

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US public US privateCanada public

and privateDutch public and private

VALUATION REQUIREMENTS: LIABILITIES

Liability discount rate

GASP: Expected return of assets

Before 2004: ERISACorridor around 4Y average of 30Y T-Bond .

2004-06: PFEACorporate bond market rate, 4Y average.

Since 2006: PPA+FAS158Corporate bond market rate (smoothing for PPA)

Before 2000 : CICA3460 Long term expected return of assets (“best estimate”)

After 2000: CICA3461Government bond rate

Before2007: PSWFixed actuarial interest rate with a maximum.

Since 2007: FTKSwap rate.

Liabilities recognized in sponsor/ gvtbalance sheet

No Before 2006: FAS87In footnotes.

Since 2006 : FAS158 Yes

Private plans: Yes since 2000 (CICA3461)

Public plans:Yes with exceptions

No

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US public US privateCanada public and

privateDutch public and

privateFUNDING REQUIREMENTS

Quantitativeriskrequirements

None None None Since 2007: FTKYes

Fixedminimumfundingrequirements

No min (0%)

1994-2006: Retirement Protection Act90%

Since 2006 : PPA92% in 200894% in 200996% in 2010100% in 2011

100% Before 2007: PSW100%

Since 2007: FTK 105% at confidence level of 97.5% with 1Y horizon.

Recoveryperiod

None Before 2006: ERISA30Y

Since 2006: PPA7Y

Usually 5YFederal plans + Alberta and Ontario plans have a max amortization period of 10Y since 2009

Before 2007: PSW10Y

Since 2007: FTK3 – 15 years depending on continuity analysis

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Methodology : Regulatory variables definitionVariable Definition Riskiness Procyclicality

Investment requirementsQuantitativeinvestmentrestrictions (QIR)

Dummy: 1 on the existence of limitson any asset class

- -

Valuation requirementsAsset valuation(Mkt Val)

Dummy: 1 if market valuation withoutdiscretion, 0 otherwise

- +

Excess liability discount rate(eLDR)

Discount rate level disclosed by thefund minus the fund’s home countrygovernment 10Y interest rate

+ ≈

Liabilities’ recognition in sponsor/ gvt balance sheet (LiabRecog)

Dummy: 1 if liabilities are recognizedon the sponsor’s (i.e., enterprise orgovernment) balance sheet

- +

Funding requirementsMin funding requirement (Fund Req)

Level of funding requirement ≈ +

Quantitative risk-based capital requirements(QRR)

Dummy: 1 on the existence ofmandatory quantitative risk-basedcapital requirements

- +

Recovery period(Recov)

Average recovery period in years + -

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Methodology : Individual and institutional variables definition

Variable Definition Riskiness ProcyclicalityIndividual characteristics

Maturity(Maturity )

Percentage of retired members - ≈

Inflation indexation(InfIndx )

Percentage of member’s benefitscontractually indexed to inflation

+ ≈

Size(Size)

Market value of Assets UnderManagement in billions of USD

+(for alternatives)

≈

Institutional characteristics

Guarantee(Guarantee )

Dummy: 1 if pension benefits arecollectively insured by a guaranteefund

+ ≈

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Panel regression analysis with the following explan atory variables

Methodology

Inst

itutio

nal F

acto

r

Fun

d C

hara

cter

istic

s

Reg

ulat

ory

Fac

torsQuantitative Investment

Restriction

Excess liability discount rate

Mark-to-market asset valuation, min funding requirements and recovery period

Liabilities in sponsor’s balance sheet

Quantitative risk-basedcapital requirements

Maturity

Indexation

Size of AUM

External guarantee

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Allocation to risky assets

� We estimate the following pooled panel regression model

Methodology

• �� is the allocation to risky assets, or its sub-categories: equities, risky fixed income, and alternatives for fund i at time t.

• Standard errors are clustered by Year

�� =∝ +1�� + 2�� + 3� �� + 4�� + 5� �� + 6�� + 7�"# �"$%�� + 8'�(�� + 9*��"�� + +��

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Procyclicality of Equity Investment

� Definition of the procyclicality measure

Methodology

,-��(/) = 110 if sign(�� -��/ )=sign(��9� )otherwise

• �� is the fund i’s allocation to risky assets at time t

• ��@ is a reference weight the fund would have if it were not procyclical

• A fund is considered procyclical if it increases its asset allocation to riskyassets in response to high performances that year (and the reverse)

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� We define two alternative definitions of the reference weight

– A full rebalancing strategy: reference weights are considered constant and equal to the fund’s average reported allocation over time

– A no-rebalancing strategy: reference weights are defined as the weights that the fund would have if it lets assets drift along with market performance

Methodology

��AB = ��CD DEFGHIGJKLDEFGHM

is the asset drift weight.

��F�NOP is the risky asset return

��Q is the total return of the fund.

��RS = 1T U ��Q

�VD

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� We estimate the following logit regression model

Methodology

• ,-��@ is the procyclicality indicator for fund i at time t

ln X ,Y,-��(/) = 1Z1 − ,Y,-��(/) = 1Z\ =] + 1�� + 2�� + 3� �� + 4��

+ 5� �� + 6�� + 7�"# �"$%�� + 8'�(��+ 9*��"�� + +��

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� CEM Benchmarking Database

– More than 800 DB pension funds

– Around 500 in the US, 250 in Canada and 80 in the Netherlands, representing respectively 40%, 90% and 30% of US, Canadian and DutchDB funds

– Yearly asset allocation and performance over 1990-2011

Data

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Pension Funds’ Measure of Procyclicality

Procyclicality measurebased on equity marketAverage over all funds

More procyclicality duringperiods of expansion

US public funds muchmore procyclical since2008

Procyclicality Measure (comparison to full rebalanci ng strategy)

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Pension Funds’ Measure of Procyclicality

Procyclicality measurebased on equity marketAverage over all funds

Evidence of procyclicalityduring the 2 crises (2001 – 2007)

Procyclicality Measure (comparison to no-rebalancing strategy)

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Results: risky asset allocation Dependent variable: Percentage Allocation to Risky Assets Equities Risky Fixed

Income Alternatives

Quantitative Investment Restrictions -0.573 (1.3)

9.490*** (1.470)

-2.740*** (1.020)

-7.320*** (1.360)

Excess Liability Discount Rate 4.670*** (0.673)

3.660*** (0.876)

-0.204 (0.253)

1.210* (0.687)

Funding, Recovery, Market Valuation -2.420 (1.810)

-8.760*** (2.180)

2.400** (1.220)

3.940** (1.880)

Liabilities Recognized in Sponsor's Balance Sheet -1.610* (0.832)

-2.690** (1.190)

-0.153 (0.166)

1.230** (0.499)

Quantitative Risk-based Capital Requirements -8.200*** (1.710)

-12.700*** (2.750)

0.691 (1.130)

3.810*** (1.290)

Maturity -2.480*** (0.414)

-3.180*** (0.377)

-0.082 (0.062)

0.779*** (0.201)

Inflation Indexation 0.648** (0.283)

-2.030*** (0.646)

-0.068 (0.099)

2.750*** (0.467)

Size 2.540*** (0.200)

-1.910*** (0.595)

0.305*** (0.094)

4.140*** (0.470)

Guarantee 7.330*** (1.240)

11.800*** (2.260)

-2.670** (1.200)

-1.760 (1.920)

Intercept 64.700*** (1.360)

57.900*** (1.260)

1.560*** (0.318)

5.230*** (0.545)

2 0.213 0.182 0.084 0.174

Adjusted- 2 0.211 0.180 0.081 0.172

Nobs. 3932 3932 3932 3932

Significance: *0.1, **0.05,***0.01

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Results: risky asset allocation (alternatives) Dependent variable: Percentage Allocation to Commo Infra RE PE, VC, LBO HF Quantitative Investment Restrictions -0.278***

(0.076) -0.263 (0.302)

-3.120*** (0.618)

-2.210*** (0.319)

-2.400*** (0.845)

Excess Liability Discount Rate -0.081 (0.051)

0.179** (0.072)

-0.351 (0.289)

1.220*** (0.290)

0.591*** (0.203)

Funding, Recovery, Market Valuation 0.230** (0.095)

0.684* (0.390)

-0.576*** (0.194)

0.777*** (0.282)

1.260*** (0.276)

Liabilities Recognized in Sponsor's Balance Sheet 0.045 (0.030)

-0.112 (0.081)

1.210* (0.635)

2.140*** (0.539)

2.630** (1.210)

Quantitative Risk-based Capital Requirements 1.410*** (0.180)

0.0305 (0.290)

2.850*** (0.537)

7.250*** (0.392)

-1.070 (0.869)

Maturity 0.0003 (0.024)

-0.005 (0.010)

0.235* (0.137)

0.238*** (0.059)

0.088 (0.151)

Inflation Indexation 0.090*** (0.023)

0.131*** (0.031)

1.200*** (0.134)

0.778*** (0.233)

0.925*** (0.159)

Size 0.098*** (0.038)

0.185*** (0.046)

1.550*** (0.120)

2.420*** (0.268)

0.316*** (0.075)

Guarantee -0.193* (0.106)

-0.525 (0.364)

-2.060*** (0.703)

-0.693 (0.490)

-1.410 (1.160)

Intercept 0.118* (0.063)

-0.234*** (0.083)

4.150*** (0.294)

-0.309 (0.295)

-0.330** (0.147)

2 0.112 0.052 0.168 0.214 0.079

Adjusted- 2 0.110 0.050 0.166 0.212 0.077

Nobs. 3932 3932 3932 3932 3932

Significance: *0.1, **0.05,***0.01

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Results: risky asset allocation (risky fixed income)s Dependent variable:

Percentage Allocation to High Yield Mortgages Quantitative Investment Restrictions -1.560***

(0.161) -1.180***

(0.134)


-0.485*** (0.066)

Funding, Recovery, Market Valuation 1.140*** (0.206)

1.260*** (0.172)

Liabilities Recognized in Sponsor's Balance Sheet 0.154* (0.086)

-0.307*** (0.072)

Quantitative Risk-based Capital Requirements 0.672** (0.277)

0.019 (0.231)

Maturity -0.042 (0.065)

-0.0406 (0.054)

Inflation Indexation 0.117* (0.070)

-0.185*** (0.058)

Size 0.174*** (0.065)

0.131** (0.054)

Guarantee -1.040*** (0.194)

-1.630*** (0.162)

Intercept 0.614*** (0.121)

0.950*** (0.101)

2 0.070 0.070

Adjusted- 2 0.068 0.068

Nobs. 3932 3932

Significance: *0.1, **0.05,***0.01

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� Regulatory factors have much more economic impact than individual characteristics, similar to institutional factors

– Significant reduction in risky asset allocation

� Risk-based capital requirements have the strongest impact

– Strong reduction in risky asset weights , especially equities – Positive impact on alternatives (especially private equity, real estate) and

risky fixed income (mainly high yield)

� The choice of the liabilities discount rate comes as the second largest impact

Results: risky asset allocation

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Results: procyclicality (comparison to full rebalancing strategy) Dependent variable: ,-� Risky Assets Equities Risky Fixed

Income Alternatives

Quantitative Investment Restrictions 0.259 (0.185)

0.990*** (0.309)

-2.030** (0.905)

-0.857*** (0.277)


0.315 (0.208)

0.581 (0.269)

0.256 (0.234)

Funding, Recovery, Market Valuation 0.221 (0.293)

-0.940** (0.419)

2.310 (1.170)

0.831*** (0.25)

Liabilities Recognized in Sponsor's Balance Sheet

-0.510** (0.228)

-0.533** (0.248)

-0.223 (0.215)

0.306* (0.185)

Quantitative Risk-based Capital Requirements -0.375 (0.419)

0.167 (0.603)

-0.718 (0.976)

-0.258 (0.420)

Maturity 0.104 (0.086)

0.008 (0.089)

0.072 (0.091)

0.014 (0.066)

Inflation Indexation 0.049 (0.109)

-0.093 (0.125)

0.211*** (0.085)

0.216 (0.135)

Size 0.203 (0.123)

-0.001 (0.151)

0.695*** (0.110)

0.238* (0.132)

Guarantee 0.021 (0.236)

0.908** (0.393)

-1.900 (1.150)

-0.731*** (0.278)

Intercept -0.486** (0.197)

0.176 (0.254)

-2.200 (0.404)

-0.819*** (0.192)

Pseudo- 2 0.024 0.027 0.074 0.019

Nobs. 3932 3932 3932 3932

Significance: *0.1, **0.05,***0.01 VIII This is 1 − �1�0, �1 is the log likelihood of the estimated model. �0 is the log likelihood of the null model with only the

constant term.

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Results: procyclicality (comparison to no-rebalancing strategy) Dependent variable: ,-^� Risky Assets Equities Risky Fixed

Income Alternatives

Quantitative Investment Restrictions -0.534** (0.269)

1.140** (0.558)

-1.640** (0.721)

-0.691 (0.468)

Excess Liability Discount Rate -0.322 (0.218)

-0.310 (0.230)

0.087 (0.290)

-0.305** (0.127)

Funding, Recovery, Market Valuation 0.484 (0.327)

-1.350** (0.534)

1.040 (1.180)

0.164 (0.477)

Liabilities Recognized in Sponsor's Balance Sheet

0.190 (0.263)

-0.374 (0.348)

0.074 (0.595)

0.375 (0.343)

Quantitative Risk-based Capital Requirements -1.030* (0.573)

0.803 (0.597)

-0.477 (1.160)

-0.575 (0.607)

Maturity -0.066 (0.071)

-0.195* (0.116)

0.117 (0.121)

-0.171 (0.111)

Inflation Indexation 0.050 (0.131)

-0.042 (0.084)

0.260 (0.173)

0.179 (0.133)

Size -0.0217 (0.213)

0.082 (0.089)

0.484*** (0.108)

0.0264 (0.194)

Guarantee -0.468* (0.279)

1.500*** (0.541)

-0.980 (1.100)

-0.493 (0.398)

Intercept -0.744* (0.400)

1.450*** (0.373)

-2.440*** (0.419)

-0.473*** (0.163)

Pseudo- 2 0.007 0.025 0.049 0.012

Nobs. 3932 3932 3932 3932

Significance: *0.1, **0.05,***0.01

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� We find evidence of procyclicality– Funds do not set their weights equal to full-rebalancing– Additional procyclicality during financial crises (asset weight decrease

stronger than implied by asset drift)

� Little evidence of regulatory impact on procyclicality– Except for quantitative investment restrictions

� Counterintuitively, risk-based regulation induced lower procyclicalbehavior– Result driven by the temporary regulatory slackening during the last crisis in

the Netherlands (extension of recovery period, suspension of pension indexation or reduction in nominal pensions, higher contribution rates allowed, etc.)

Results: procyclicality

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� Our objective: quantify the importance of regulatory factors on top of individual / structural characteristics of the funds

� Regulation plays a strong role in pension funds’ asset allocation choices, compared to institutional / individual funds’ variables

� All regulatory measures (asset valuation, funding requirements) and in particular risk-based capital requirements decreased the overall risky asset allocation

� Strong reduction of equities , but paradoxically risk-based regulations led to an increase in alternatives , especially real estate and private equity

Conclusion

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� We find evidence of some form of procyclicality, more pronounced during financial crises

� Counterintuitively, we do not find that risk-based regulation induced a more procyclical behavior– Unique to the Netherlands: the DNB authorized numerous waivers to the

standing regulation during the Subprime crisis (especially extension of the recovery period) to assist pension funds

– This argues for a « dynamic » setting of regulatory rules ?

Conclusion

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An investment management company approved by the French Securities Authority(Autorité des marchés financiers) under no. GP 04000036

Registered office: 90 boulevard Pasteur 75015, RCS Paris no. 437 574 452

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