1. University Rostock, Germany
The Effects of Liberalization and Deregulation on the Performance of Financial Institutions: The Case of the German Life Insurance Market
Lucinda Trigo Gamarra
University Rostock, Germany
XXXIII SAE
Zaragoza, Dec, 11-13, 2008

2. Liberalization of European Life Insurance Markets
Three European Directives on Life Insurance (1979/1990/1992)
Freedom of establishment and services
Home country supervision (‚single license‘ principle)
Abolition of material price and product regulation
Aims:
Fostering of inter- and cross-country competition
Increase efficiency of insurance markets
Increase customers‘ welfare by larger product variety and more competitive prices
Motivation

3. The German Life Insurance Market
Situation before liberalization in 1994
Ex-ante approval of contract conditions and new contract types
Price regulation (cost-plus regulation)
Limited competition (Exemption from competition law (GWB))
Few product innovations
Stable, fairly high premium levels
Competition mainly on service: Intense level of selling activities
Aim of this study: Analysis of the Liberalization Effects
Changes in cost and profit efficiency after liberalization
Calculation of Total Factor Productivity (TFP) growth
= technical change + cost efficiency change + scale efficiency change
Motivation

4. Previous Evidence and Own Contribution
Hypotheses
Previous Evidence and Own Contribution
Methodology and Modelling Approach
Data Set and Variables
Results
Conclusions
Outline

5. Changes in cost and profit efficiency
 / 
Cost efficiency (CE)
Realization of cost-saving potentials due to increased competition
Better risk diversification
Adaptation and implementation costs to changes in distribution channels, internal communication, technologies
Profit efficiency (PE)
Increased competition  realization of unused profit potentials
Relaxed investment rules
Temporarily price-setting power caused by product and service innovations
H1 Cost and profit efficiency in the German life insurance industry increased during the observation period.
H2 Cost efficiency decreased, while profit efficiency increased.
Hypotheses 

6. Scale efficiency and technical change
Scale efficiency (SE) (H3)
Market consolidation via M&A activities
Realization of economies of scale
Technical change (H4)
Labour-saving potentials of progress in information technologies during the 90‘s 
Hypotheses 

7. Previous Evidence and Own Contribution
Hussels and Ward (2004)
30 randomly chosen German life insurers
Balanced panel
Non-parametric Malmquist DEA
Small increases in cost efficiency and positive technical change
Mahlberg and Url (2007)
Whole German insurance industry
No differentiation between insurance lines
Large increases in scale efficiency
Huge swings in technical change
Previous Evidence and Own Contribution

8. Contribution of this study
Sample covers whole life insurance industry
Unbalanced panel accounts for possible effects by market entries/ exits
Incorporation of profit efficiency change
Firms‘ revenues are considered
Liberalization effects on firms‘ profitability are taken into account
Previous Evidence and Own Contribution

9. Technical cost efficiencyx2 A 
Methodology B 
L(y)
isoquant x1

10. TFP change Methodology y F(x) t+1 CRS F(x) t+1VRS MPSS t+1 F(x) t CRS
F(x) t CRS
F(x) t VRS x
MPSS t 
A t+1 
y t+1 C
x t+1 SE 
A t+1 SE
Technical change
x t+1* 
A t+1*
Methodology
x t 
y t
A t B
x t SE 
A t SE 
A t *
x t *

11. Profit efficiency y * ' E y * y D D x x D x* Methodology PE = / *
Methodology
y D  D
PE = / *
- ∞ ≤ PE ≤1
production frontier x
x D x*

12. Parametric distance frontier
Stochastic input distance translog frontier
Panel estimator: inefficiency uit varies freely through time and across firms
Firm-individual heterogeneity is accounted for by „true“ Fixed Effects estimator (Greene, 2005)
Firm-individual technical cost efficiency (TCE) estimates:
Estimation approach
uit = E(uit| εit) => TCEit = [exp(-uit)]

13. TFP change – calculation and decomposition
Estimation approach
Technical cost
efficiency change
Scale efficiency change
Technical change

14. Profit Efficiency
Derivation of (alternative) profit efficiency according to Kumbakhar (2006):
, where
, and
Profit efficiency change (PEC):
PEC= ln (PEi2/PEi1)
Estimation approach

15. Variables Main services provided by life insurers:
Risk pooling/ risk bearing
Financial intermediation
Inputs
Operating expenses
Equity costs
Outputs
Incurred benefits (net of reinsurance)
Additions to reserves (net of reinsurance)
Bonuses and rebates
Revenues
Earned premiums (net of reinsurance)
Investment income
Variables and Data Set

16. Data
Firm-individual information obtained by perodically published industry reports
Observation period
Unbalanced panel
Variables and Data Set

17. ML estimates – Input distance frontier
Results

18. Mean Technical Cost and Profit Efficiency
Results

19. TFP growth and decomposition
Year
Technical Change
Technical Cost Efficiency Change
Scale Efficiency Change
TFP Growth
Profit Efficiency Change
1995/96
4.031
5.429
12.715
22.175
0.017
1996/97
5.022
-2.304
12.066
14.784
1.088
1997/98
6.017
3.581
6.219
15.817
1.703
1998/99
7.081
-7.616
5.108
4.573
-2.402
1999/2000
7.835
2.100
6.264
16.200
1.664
2000/01
9.186
5.267
-1.604
12.849
2.063
2001/02
10.605
-9.408
-1.122
0.075
-1.535
Mean
7.111
-0.421
5.664
12.353
0.371
7.289
-0.214
24.265
31.339
1.518
Results

20. Conclusions Technical cost efficiency largely unchanged
Profit efficiency largely unchanged
No clear efficiency gains by liberalization
Scale efficiency increases by 5.7 percent on average
Effect of market consolidation under increasing returns to scale
Positive technical change of 7.1 percent on average
Largest contribution to positive TFP growth
Consequence of innovations in IT
Liberalization mainly causes size effects
Reasons
Foreign insurers prefer M & A‘s
Cross-border services remain limited
Results