Abridged English version of the SCHUFA Credit Compass 2008

Debt Compass 

Empirical Indicators of Private Debt 

and Over-indebtedness 

Published by SCHUFA Holding AG

2008 Debt Compass 

Debt Compass 

Empirical Indicators 

of Private Debt 

and Over-indebtedness 

(Abridged Version) 

Published by SCHUFA Holding AG

Contents 

Debt Compass | Contents 

Foreword 7 

I Overview of Analyses and Core Findings 8 

II Retrospective Glance: Debt Compass 2003, 2004, 2005, 2006, 2007 13 

A Representative Evaluation of the SCHUFA Data 

(SCHUFA Holding AG) 

A-1: Basic Analysis 19 

1. Trends in Private Debt 22 

2. Regional Evaluations 30 

3. Risk Model 33 

A-2: Private Debt Index (PDI) 49 

1. Design of the PDI 51 


– Evaluation by Federal State 

– Evaluation by District 

– Evaluation of Cities 

3. Forecast 2009 61 

4. Tabular Overviews 64 

3

List of Abbreviations 

ALG Unemployment benefit (Arbeitslosengeld) 

GDP Gross domestic product 

BSHG Federal Social Assistance Act (Bundessozialhilfegesetz) 

DIW German Institute for Economic Research (Deutsches Institut für Wirtschaftsforschung) 

EU-SILC European Union Statistics on Income and Living Conditions 

EV Oath of disclosure (Eidesstattliche Versicherung) 

EVS Sample survey of income and expenditure (Einkommens- und Verbraucherstichprobe) 

HLU Social assistance (Hilfe zum Lebensunterhalt) 

IJF Institute for Youth Research (Institut für Jugendforschung) 

InsO Insolvency Act (Insolvenzordnung) 

OECD Organisation for Economic Co-operation and Development 

PDI Private Debt Index 

SCHUFA Schutzgemeinschaft für allgemeine Kreditsicherung 

SGB Code of Social Law (Sozialgesetzbuch) 

SOEP The German Socio-Economic Panel Study (Sozio-oekonomisches Panel) 

Tab. Table 

ZPO Code of Civil Procedure (Zivilprozessordnung) 

Debt Compass | List of Abbreviations 

5

Foreword 

Dear reader, 

Debt Compass | Foreword 

The 2008 Debt Compass appeared in the middle of the global credit and financial crisis, which 

many economists and historians are calling the deepest downturn since 1929. The crisis is 

believed to have originated in the United States, where mortgages were granted to people with 

little creditworthiness. The commercial downturn in the U.S., which began around 2005, and 

the subsequent increase of the U.S. prime rate set off a chain reaction. Low-income borrowers 

could no longer make the mounting payments for their variable interest rate loans with much 

shorter terms. 

The failures in the U.S. mortgage market have clearly demonstrated that responsible lending 

and reliable credit information not only protect lending agencies from payment defaults, but 

also consumers from over-indebtedness. 

With the Debt Compass – now in its sixth year of publication – it is becoming clear that lenders 

in Germany are acting cautiously. This is compounded by the communication system between 

lenders and borrowers within the German credit industry and reliable creditworthiness information. 

The average default rate for consumer credit recorded in the SCHUFA data portfolio has been 

relatively stable for many years (2007: 2.5 %), with an increase of about one half of a percentage 

point since 2003. The number of over-indebted private households has also been at a constant 

level for years (2003: 2.8 million and 2007: 2.8 million after a temporary increase to 3.0 million). 

Since the first edition of the Debt Compass, the percentage of individuals for whom SHUFA has 

only recorded information concerning contractually compliant behaviour has remained consistent 

at over 90 percent. For these individuals there is no evidence of critical debt levels or a high 

occurrence of payment defaults. 

But since the German economy will be affected by the economic crisis, the extent of which is 

not yet known, further developments remain to be seen. The prognoses of SHUFA for 2009 do 

not presently forecast any serious increase of critical over-indebtedness on a nationwide scale. 

Nevertheless, the relatively stable position of indebtedness and over-indebtedness in Germany 

that has been apparent for many years should not lead people to twiddle their thumbs. On the 

contrary, it is essential that we remain active in our efforts to investigate the phenomenon of 

over-indebtedness, and to develop preventative approaches. With its Debt Compass, SCHUFA 

will continue to make a contribution to these objectives. 

I wish you informative reading 

Rainer Neumann 

Chairman of the board of SCHUFA Holding AG 

7

Debt Compass | Overview of Analyses and Core Findings 

8 

I Overview of Analyses and Core Findings 

In order to identify reliable trends, relative and objective indicators will be examined with the Debt 

Compass as a platform for over-indebtedness research. These indicators are measurable, representative 

for the entire population of the Federal Republic of Germany, and can be regularly collected 

as an extension of official social reporting. 

Judging the extent of private over-indebtedness solely on the basis of private insolvency cases 

(absolute over-indebtedness) is inadequate. Relative and absolute private over-indebtedness have 

mostly developing natures, for which the delivery of an affidavit or the initiation of a private insolvency 

proceeding represent merely the endpoints – inability to pay or over-indebtedness. The 

Debt Compass examines the critical junctures of indebtedness. Against this background, SCHUFA 

has developed a risk model with various “risk levels”. At the same time, this model is the basis 

for the design of the Private Debt Index (PDI). The PDI shows in which geographical regions the 

critical indicators of private debt have grown especially strongly. 

As publisher of the Debt Compass research platform, SCHUFA presents five analyses in the 

current 2008 Debt Compass: the analysis of SCHUFA data (Sub-Analyses A-1 and A-2) containing 

examinations of SCHUFA Holding AG on the basis of its total data portfolio of information 

on approximately 65 million individuals over 18 years old. This comes close to a complete census. 

Analyses B, C, D and E are all external studies which are totally independent of SCHUFA and its 

data. None of the findings in the external Analyses are findings or conclusions of SCHUFA, but 

are exclusively the findings, pronouncements or position papers of the authors or the involved 

agencies and institutes which are cited in each case. 

Analysis A: 

Representative evaluation of SCHUFA data 

The current SCHUFA data portfolio includes around 433 million data records from around 

65 million native adults in Germany. Differentiated by age group, county and Federal State, 

the data was made anonymous for the Debt Compass, thus allowing for statistical reporting 

on the extent of instalment loans, loan defaults and payment defaults reported by clients. 

The four risk levels, which are intended to depict the procedural nature of over-indebtedness, 

are an attempt to ascertain the number of individuals who are over-indebted or at risk of 

becoming over-indebted. 

The Private Debt Index developed by SCHUFA gives an overview of how strongly critical indicators 

for private debt appear in various regions of Germany. Moreover, it forecasts how the individual 

regions will develop to the end of 2009. This prognosis on the Federal State and county level is 

unique in the field of over-indebtedness research.

Core Findings 


The condition of private debt and over-indebtedness in Germany presents itself in the years 

2005 through 2007 as relatively stabile. Even given the forecast for 2009, up to now no 

critical development are expected. 

The SCHUFA Private Debt Index (PDI) remained static in 2008 (reporting date of 06-30-2008) 

with respect to the previous year. Compared to 2007, in the middle of 2008 five Federal States 

exhibit a slight decline (improvement) of PDI, eight a slight rise (worsening) and three Federal 

States exhibit no change of PDI. 

The current calculations of PDI for all 429 counties show that over-indebtedness risks of private 

individuals are not accumulating in any particular region of Germany. The current forecast shows 

a PDI decline in 186 counties, an increase in 218 counties and no change in 25 counties. 

The percentage for individuals, for whom information is available to SCHUFA only regarding 

contractual payments, lies above 90 percent once again (91.8 %) for the year 2007. 

The current average credit obligations (remaining debt) in the area of consumer credit is 8,078 

Euro in 2007, nearly unchanged in comparison to the previous year (8,087 Euro in 2006). 

Even failed consumer credit as a percentage of all loans is moving at a relatively stable pace, 

with an average of 2.5 percent showing only a minimal increase (2005: 2.3 % and 2006: 2.4 %). 

Thus in 2007 more than 97 percent of all loans were attended upon according to contract. 

The maximum failure rate lay in the age group of 25- to 29-year-olds at 3.3 percent. 

The growth rate of individuals with hard negative indicators (e.g. information concerning the 

delivery of an affidavit or ongoing consumer insolvency proceedings) is decreasing in nearly all 

age groups. In the younger age groups, they have actually decreased somewhat. 

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EXTERNAL ANALYSES 

Analysis B: 

Evaluation of debt advisor data 

The Statistische Bundesamt (Federal Statistical Office Germany) has organized voluntary overindebtedness 

statistics since reporting year 2006, in order to further develop social reporting data 

records. The statistics presented in the excerpts draw on data from debt advisory services as well 

as figures from official insolvency statistics. Although individuals who visit a debt advisory service 

need not be over-indebted, nevertheless this survey can clearly improve data records regarding 

the situation of individuals and households who are in financial difficulties or even over-indebted. 

In reporting year 2007, 212 (of 950) advisory services in Germany have taken part in the voluntary 

survey and supplied anonymized details for approximately 57,000 individuals. The analysis 

yields information about the triggers of over-indebtedness and about the group of people that 

is most likely to be affected by over-indebtedness. In addition, it examines the socio-economic 

patterns of individuals who sought advice, as well as the average amount of indebtedness. 

Core Findings 

From 1999 to the present, nearly 500,000 consumers have filed for insolvency hoping to overcome 

their financial difficulties. The number of proceedings rose from year to year up to approximately 

105,000 petitions in 2007, of which only a few were rejected. At year's end in 2007 

and in the first half of 2008, however, a slowdown became apparent for the first time since the 

implementation of the 1999 Isolvenzordnung (German Insolvency Act). 48,000 consumer insolvencies 

were granted in the first half of 2008, 7 percent fewer than the previous year. Debts 

averaged 59,000 Euro, roughly a third of the average sum for 2001. In 2007, 41 percent of individuals 

who sought debt advice were less than 10,000 Euro in arrears to their creditors. Just 

short of 8 percent of individuals who sought advice had debt levels that exceeded 100,000 Euro. 

Among individuals who neither had mortgage loans nor were independent of debt, just under 

half of all debts were to banks in the form of overdraft credit or instalment loans. Following far 

behind were debts to collection agencies (12 %), to public creditors (7 %), to private individuals 

(4 %) and to landlords (4 %). A further cause is uneconomical household management (9 %), 

among which failed home loans were cited only in relatively few cases (4 %) as the leading cause 

of over-indebtedness. 

Analysis C: 

Trend in the extent of over-indebted private households in 2007 

Over-indebtedness analyst Gunter E. Zimmermann analyzes the number of relatively over-indebted 

households on the basis of data from the 2007 Sozio-oekonomische Panel (SOEP) (The German 

Socio-Economic Panel) and demonstrates the trend of private over-indebtedness in Germany from 

1997 to 2007. It is emphasized that the SOEP data are representative for the entire population 

and the analysis does not rest on private insolvency alone. A distinction is made between overindebtedness 

on the basis of consumer debt and/or mortgage loans. In addition upper and lower 

limit of over-indebtedness is described, in order to emphasize that the number of over-indebted 

private households depends on the definition: depending on whether the cost of living is based 

on social assistance rates (lower limit of over-indebtedness) or on the rates used for exemptions 

from attachment (upper limits of over-indebtedness), different total numbers of over-indebted 

households in Germany are generated.

Core Findings 


The number of relatively over-indebted private households with consumer debt and/or mortgage 

loans has slightly diminished, from 2.9 million in 2006 to 2.8 million in 2007. The number of 

relatively over-indebted private households with consumer debt only, and with living expenses 

measured according to the rates used for exemptions from attachment, has remained about the 

same compared to 2006 with around 1.6 million households nationwide. When the measurement 

of relatively over-indebted households is not based on the exemption from attachment rates, but 

rather on the social assistance rates, the number of relatively over-indebted households in 2007 

changes to 970,000. In the previous year, the total was 930,000 households, although the increase 

is partly due to the emendation by the Statistische Bundesamt in 2007 of the number of 

private households in Germany. 

Analysis D: 

Poverty and over-indebtedness 

This comparative study by Gunter E. Zimmermann on the basis of data from the 2007 SOEP 

dealt with over-indebtedness of households that are income-poor or at risk of poverty. 

The central questions are: What is poverty and how should it be measured? Are households in 

danger of poverty commonly in debt or over-indebted? In which income groups is there a disproportionately 

high risk of over-indebtedness? What are the characteristics of households that 

are in danger of poverty or over-indebted? 

For an analysis of the connections and/or the possible reciprocal effects between poverty and 

over-indebtedness, the analyst differentiates households according to their income levels: 

1. Households whose household income (before debt) is less than the proportionate limits for 

exemption from attachment. 

2. Households which are designated as income-poor or at risk of poverty, according to the 

EU standard. 

3. Households with a net income over the limit for exemption from attachment (and therefore 

not income-poor), whose disposable income after subtracting payment obligations from debts 

fall under the limit for income-poor poverty. 

Core Findings 

There isn't “the” definition, either for poverty or over-indebtedness, since necessity always 

demands that normative value judgments slip into the definition. Poverty or over-indebtedness 

are present if the net income of the relevant parties (less the payment obligations from debts, in 

the case of over-indebtedness) falls below a socio-politically defined (normative) subsistence level, 

whereas legislators in Germany have given greatly varying definitions for the subsistence level 

for poverty and over-indebtedness. Private households whose net income lies under the limits for 

exemption from attachment, as well as private households at risk of poverty or income-poor, are 

neither more commonly nor less commonly indebted than other income groups. This indicates 

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12 

that fundamentally every income group in Germany has access to credit. Certainly among private 

households with consumer credit, the portion of over-indebted households that are at risk of 

poverty or income-poor is disproportionately high. 26 percent of all over-indebted households 

with consumer credit (upper limit for over-indebtedness) are income-poor. Nearly three-fourths 

of households that are over-indebted and 

Analysis E: 

Is the impoverished population in Germany excluded? 

The analysts Petra Buhr and Stephan Leibfried give an overview of concepts in poverty research 

and specifications of income poverty. They pursue the question of whether poverty inevitably 

leads to social exclusion. Among other things, the analysis discusses “consistent poverty”, by 

which is meant the coincidence of income poverty with shortages in many other areas of life. 

While consistent poverty is an indicator for exclusion processes, there are inconsistent conditions 

that cross the boundaries between poverty and non-poverty. 

Core Findings 

There are partial and intermittent exclusions as well as blurred transitions between poverty and 

non-poverty. This speaks for a gradational, gradual and dynamic concept of exclusion and against 

a sharp dividing line between “inside” and “outside”. Even if the mobility of the impoverished 

population has lessened in recent years and smaller rises are more common than larger ones, 

poverty is not a consistently self-reinforcing process with no way out. The majority of the poor, 

even if they are poor for a long time, actively cope with their situation, have the prospect of 

escape and retain the ability to act. In this respect the “connectivity” to non-poverty, normal 

biography and normal conduct of life is preserved even with long-term poverty.

2003 Debt Compass 

Debt Compass | Retrospective Glance 

II Retrospective Glance: 

Debt Compass 2003, 2004, 2005, 2006, 2007 

The first Debt Compass published in November of 2003 was the start of an analysis series to be 

updated and continually expanded on an annual basis. “The Debt Compass has been designed 

to contribute to a better understanding of credit-based activities, show new orientation opportunities 

in the German credit landscape and encourage further research initiatives”, said Hans-Peter 

Krämer, former Chairman of the Supervisory Board of SCHUFA Holding AG and Rainer Neumann, 

Chairman of the Executive Board of SCHUFA Holding AG. 

As a credit facilitator and credit accelerator, and as an institution with more than 80 years of 

tradition, SCHUFA considers the enhancement of research into the causes of private over-indebtedness 

its duty. The anonymous analysis of the SCHUFA data portfolios is intended to contribute 

to making the public discussion more objective in order to also derive preventive aspects. 

The studies from the first period of observation from 1999 to 2002 concerning payment and loan 

defaults showed that there had not been any significant increase in payment and loan defaults 

in any of the age groups or counties. It was still possible, however, to establish marked payment 

defaults, especially in the younger age groups, in individual regions as well as in the case of 

smaller loans and in the telecommunications industry. The central task was thus to check in the 

subsequent years how the observed findings and trends would change. 

It became clear in the discussion that over-indebtedness always involved payment defaults, but 

one payment problem did not necessarily mean over-indebtedness. This led to a number of 

different questions. To what extent is the payment default an indication of temporary or permanent 

liquidity problems? What factors have an influence on the payment defaults of private 

individuals, and what instruments or indicator bundles are appropriate for establishing the overindebtedness 

situation of private German households? The large degree of interest within the 

wider public has illustrated the necessity of an interdisciplinary dialogue between experts in order 

to obtain the most complex and objective picture possible of the private over-indebtedness in 

Germany. 

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14 


The numerous requests from the public, practitioners and researchers received by SCHUFA since 

the publication of the first Debt Compass has encouraged SCHUFA to further differentiate and 

expand the Debt Compass. It became clear as early on as during the preliminary work on the first 

Debt Compass that many sub-aspects would have to be taken into account on a broad data basis 

to be able to more comprehensibly understand private debt and over-indebtedness. The central 

task for the 2004 Debt Compass was thus to supplement the previous customary indicators of 

private over-indebtedness more broadly. 

The SCHUFA data portfolio was made anonymous and evaluated statistically with respect to 

the loans, defaults on loans and payment defaults reported by clients. The interactive map of 

Germany with geographical peculiarities concerning debt and a risk model to differentiate 

between risk levels and degrees debt and over-indebtedness was developed for the first time. 

Developments concerning the amount of credit, payment defaults and risk groups could be 

presented clearly and on a national level. 

On the basis of further representative studies, additional perspectives from over-indebtedness 

research were taken into account. Gunter E. Zimmermann employed the term over-indebtedness 

on the basis of the Attachment Schedule and the Federal Social Assistance Act. The market 

research institute MANAGEMENT consult collected information on risk situations in representative 

household interviews on the topic of how to deal with private loans. Winfried Hacker introduced 

loan servicing self-management as a central category to examine ways out of debt. The international 

comparison by Udo Reifner and Helga Springeneer helped to categorize the analyses 

of the Debt Compass on a global level.


Schulden-Kompass | Rückblick 

With the continual, anonymous, full collection of data and the testing of new research approaches, 

the Debt Compass expanded debt and over-indebtedness statistics from Germany to include 

reliable indicators. The Debt Compass has established itself as basic research and orientation tool 

in research, politics and the lending industry. 

The third edition allowed for statements on trends over a longer period of three years. It was 

observed that the percentage of defaulted instalment loans with respect to all current borrowings 

had increased across the board form 2002 to 2004. The rate of default was low in all of the three 

years, however, at a maximum of 2.8 %. Approximately 2.6 million of the 62 million individuals 

registered in the SCHUFA data portfolio may be classified as being in risk of over?indebtedness 

or as being over-indebted because hard negative indicators such as the delivery of an oath of disclosure 

(Eidesstattliche Versicherung = EV) or the initiation of personal insolvency proceedings 

(PI) existed. 

In supplement to the analyses of the preceding years, context indicators specific to individuals 

and households were included in external studies in order to form a broader circle of indicators 

and to be able to make more representative statements on the social profile of the indebted and 

over?indebtedness individuals and households. Udo Reifner and Gunter E. Zimmermann have 

studied context indicators on the basis of the Sozio-oekonomisches Panel (The German Socio- 

Economic Panel) with more than 12,000 households and just under 24,000 data records and 

300 data records by the Debt Counselling Centres in Hamburg and Wilhelmshaven using CAWIN 

software. 

It became clear that there is no such thing as “the” person who is in debt or is over-indebted. 

The social profiles, that is, the characteristic features of the people in question are too diverse. 

Furthermore, the analyses showed that the economic community and the position of the indebted 

individuals within a household are central factors for determining whether a debt process 

will lead to over-indebtedness. 

Another emphasis in 2005 was an extensive evaluation of the debt and over-indebtedness of 

young adults between the ages of 18 to 24 because debt and over-indebtedness seem to be 

increasing amongst young adults, according to information from the Debt Counselling Centres. 

The extent to which debt in young adults can trigger the risks of over-indebtedness or the start 

of a “career in over-indebtedness” was examined. In a pilot study, Dieter Korczak demonstrated 

the connections between one’s family origins and the later occurrence of over-indebtedness on 

the basis of the detailed debt biographies of young adults. 

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16 


In 2006, for the first time, SCHUFA developed the so-called Private Debt Index (PDI). As a statistical 

key figure, the PDI measures the extent of critical indicators of private debt in Germany’s 

16 federal states and 439 counties. 

Calculations of the PDI for Germany in 2005 show a total increase of 4.1 percent. It was clear, 

however, that compared to previous years’ increase of 6.6 percent between 2003 and 2005, 

the increase between 2005 and 2006 was, with 2.5 percentage points, significantly lower. 

On the basis of the socio-economic panel (SOEP), Gunter E. Zimmermann calculated in an external 

analysis the development of over-indebted households with consumer loans and mortgages in 

Germany. This analysis showed a total of about 3 million over-indebted households. Compared 

to the previous year, the number of households thus remained at a constant level. In the analysis 

based on those households that were over-indebted with consumer loans alone, however, there 

was a significant decrease. Here, in 2005, the number of households that were over-indebted as 

a result of consumer loans was between 1.0 million and 1.9 million whereas in 2004 the total 

was between 1.3 million and 2.9 million households. 

With an external pilot study from the Berlin Institute for Social Research (BIS) and on the basis the 

2006 pre-test, served as an initial analysis for the SOEP 2006 the debt indicators were expanded 

through the addition of subjective evaluations. In addition to the usual social data (age, sex, education, 

way of life, etc.) personality characteristics were tested along with other soft indicators 

(account overdraft, length of the account overdraft, etc.) which could indicate problems in handling 

money. The study determined, among other things, that there is no connection between 

household income and account overdrafts. 1 According to the BIS, an important element for overcoming 

difficult financial situations is social integration. 

The Institute for Youth Research supplemented the analyses of the Debt Compass 2005 on young 

adults (18 to 24 years of age) with a study on the debt behaviour of youths (10 to 17 years of 

age). The Youth Study attests to a greater amount of financial competence for the 1,000 interviewees 

than had been suspected. Particularly positive were the findings on saving behaviour. 

84 percent of those interviewed had saved an average of EUR 1,000. It was also interesting that 

the debt of those youths interviewed was independent of their social situation. 

1 Today the Institute for Youth Research is part of the Synovate market research group and is called Synovate Kids + Teens.



The focus of the Debt Compass 2007 was on trends related to the Private Debt Index (PDI). 

The PDI is an instrument that provides information on how critical indicators of private debt in 

Germany are developing. According to the index, from the end of 2006 until the first half of 

2007, ten federal states showed a PDI decrease. This means that, in these federal states, the 

critical indicators of private debt have decreased. At the county level too, a fall in the PDI was 

observed in the majority of counties. 

For the Debt Compass 2007, SCHUFA calculated a forecast of the PDI as of December 31, 2008 

at national and county levels. While in the overall national average 2007 as compared to the 

previous year a stagnation in the critical indicators of private debt was observed, the forecast for 

the end of 2008 signalled, for the first time, a decrease in the PDI. Over-indebtedness researcher 

Gunter E. Zimmermann investigated, in an external analysis on the basis of the data from 

the Socio-Economic Panel (SOEP) 2006 the development of over-indebted private households in 

Germany. He was able to show that the number of households affected by over-indebtedness 

with consumer loans and/or mortgages in 2006 was 2.9 million. This corresponds to a 7.3 percent 

share of all households. It was possible to show that – insofar as only the debt from consumer 

loans is concerned – in 2006 the number of over-indebted private households decreased 

to about 1.6 million and the share of all households decreased to 4.2 percent. 

In another external study, scientists Wolfram Backert and Götz Lechner described the socio-demographic 

background of people in consumer insolvency proceedings as well as the causes of the 

over-indebtedness. Their analysis, on the basis of a primary survey with over 1,600 persons who 

had filed for private insolvency, showed that insolvent persons are neither better nor worse education 

than the rest of the population. When asked, the main reasons given for the insolvency 

were unemployment, loss of financial overview as well as separation/divorce. The loss of financial 

overview was a surprising result of the cause research. 

As a result of the deepening discussion that the debt compass intensifies year for year with 

the expert public, it has become particularly clear that private over-indebtedness cannot be put 

at the same level as the submission of an oath of disclosure (Eidesstattliche Versicherung = EV) 

or private insolvency. Because over-indebtedness starts before one of the hard negative indicators 

is reached, consumers registered on the basis of private insolvency statistics make up only 

a small part of the over-indebted population. Overdue payments can also not be equated with 

over-indebtedness. Since over-indebtedness, or the threat of over-indebtedness, is the result of 

an entire range of factors and life situations, it remains a matter of systemizing the complex 

connections so that they can then be measured. 

17

Debt Compass | A | Sub-Analysis A-1 | Content 

Analysis A: 

Representative Evaluation of the SCHUFA Data 

SCHUFA Holding AG 

Sub-Analysis A-1: Basic Analysis 

1. Trends in Private Debt 22 


3. Risk model 33 

3.1 Risk model and indicators of the risk levels 

3.2 Development of risk levels from 2002 to 2007 

3.3 Regional view of the risk levels – All private individuals 

3.4 Regional view of the risk levels – Young adults 

19

Debt Compass | A | Sub-Analysis A-1 | Introduction 

20 

Introduction 

Over-indebtedness research in Germany lacks national, representative data acquisition to cover 

private debt and over-indebtedness. Because regular and full collection is impossible, the findings 

that have so far been obtained in Germany result from a variety of diverse data sources and research 

approaches. In parts only based on data from debt counsellors or debt collection bureaus, 

they merely reflect a section of private situations of over-indebtedness. 

Moreover, statements on over-indebtedness of private households have so far only been possible 

based on projections. As a result, the figures on over-indebtedness partly vary and give rise 

to different interpretations. That is why SCHUFA, with a representative data portfolio of around 

65 million adult individuals and 433 data sets of credit relevant information, makes a singular 

contribution to the current reporting on private over-indebtedness in Germany. 

Analyses based on individuals: important supplement to over-indebtedness research 

While the public discussion about private over-indebtedness primarily focuses on private households, 

SCHUFA’s analyses place the emphasis on trends in critical debt situations of adult individuals. 

The focus on private individuals is important as the percentage of single-person households 

is relatively high at around 38 percent and continually increases. 

In addition, any private individual with critical debt carries this financial burden into a multipleperson 

household. It is all the more important to be able to present a picture of the debt trends 

of private individuals. The data portfolio used to calculate the analyses is nearly a full collection. 

Statements on over-indebtedness of private households, however, have so far only been possible 

based on projections. 

Over-indebtedness situations are caused by a combination of numerous factors. Companies connected 

to SCHUFA report extra-judicial defaults of financial, commodity or service credits. These 

defaults can be interpreted and analysed as so called “soft” early warning indicators for the 

danger of over-indebtedness. Moreover, SCHUFA receives judicial information on such kinds of 

default as presented by an oath of disclosure or the initiation of personal insolvency proceedings. 

But these “hard“ indicators are just the ending of the process leading to over-indebtedness. 

So it is all the more important to develop instruments for showing reliably the first indicators of 

a critical financial situation of the population. 

Trends in private debt and the dynamics of over-indebtedness 

In the following chapters, SCHUFA introduces its current empirical results on the indicators for 

private debt and over-indebtedness. Divided according to age group, county and federal state, 

the SCHUFA data allows for statistical evaluations about the amount as well as the default of 

consumer credits. As it is primarily banks that are the creditors of over-indebted persons, and 

consumer credits have a higher default risk, monitoring consumer credits is an interesting issue 

for the over-indebtedness research.


The so-called risk model allows for the examination of the mobility of over-indebtedness based on 

SCHUFA’s data portfolio. It addresses the question whether critical situations of over-indebtedness 

become more strained over a period of five years or whether there are ways away from the risk 

of over-indebtedness or actual over-indebtedness. 

Forecast of the Private Debt Index (PDI) 

In view of the wealth of differing information on the nature of private debt and over-indebtedness 

in Germany, the PDI is an important barometer on the over-indebtedness situation or overindebtedness 

risk of private individuals in the German regions. 

A forecast of the PDI for the end of 2009 is singular in the monitoring of private debt and overindebtedness 

trends. Not only does the PDI show the extent to which critical indicators of private 

debts have increased or decreased in the various regions or counties in Germany in the current 

period until the first half of 2008. In addition, the PDI forecast provides information on the future 

development of critical indicators of private over-indebtedness. 

The sub-analyses A-1 (Trends in private debt) and A-2 (Private Debt Index) are based on SCHUFA’s 

full data portfolio as of the reporting dates December 31, 2007 and June 30, 2008. This data was 

rendered anonymous and exclusively evaluated for the 2008 Debt Compass. 

21

Debt Compass | A | Basic Analysis A-1 | 1 

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The average debt 

obligation in the age 

group 40 to 44 rises 

in the current 

observation period 

from 8.715 Euro (2005) 

to 8.983 Euro (2007). 2 

1. Trends in Private Debt 

The average credit obligation of young adults declines 

Current credit obligations separated by age group 

Age group 

* Average of current credit obligations for all persons (over 18 years) 

© 2008 SCHUFA Holding AG, all rights reserved 

Chart 1.1 

Chart 1.1 shows the change in average residual debt from consumer loans in the years 2005 to 

2007, broken down by age group. The information bears exclusively on individuals in the SCHUFA 

data portfolio who are currently indebted. Mortgage loans and lease agreements have not been 

included. 

Collectively, the average credit obligations have declined slightly from 2006 to 2007. This corresponds 

with observations of economic activity, which indicate that consumers were showing restraint 

in 2007. The three-year observation period shows a stagnating development among young 

adults (18 to 24 year olds) as well as all individuals under 35. 

Please note that the analysis is a ranking of individuals and not of households. The individuals 

could be either members or heads of households. The average debt burden is an expression of 

economic activity. No conclusions can be drawn from it concerning possible over-indebtedness 

or risk of over-indebtedness. 

2 For reasons of clarity one single age group was selected in all reader helps.

i 

Reader help: 

The amount of all 

standing loans in the 

age group 40 to 44 years 

old averaged 10,658 Euro 

in 2007. The amount 

of all defaulted loans 

averages 12,142 Euro. 

Default volumes increase with age 

Average extent of all standing and defaulted loans 

arranged according to age group, 2007 

* Average of all standing loans in 2007 

* Average of all defaulted loans in 2007 


Chart 1.2 


As in the previous chart (chart 1.1), which shows the development of residual debt in the sample 

period of individuals with consumer loans, chart 1.2 displays the average amounts of all standing 

and defaulted consumer loans per age group. In comparison to chart 1.1 the loans shown here 

are higher, since this examination displays the amount of the loans taken out, and not the residual 

debt after partial payment. It is notable that with respect to the younger age groups the 

amount of standing loans is greater than the amount of defaulted loans. On the contrary, starting 

with the 25-to-29 age group the amount of defaulted loans is higher than the amount of standing 

loans. 

Once again, all data corresponds to the entire SCHUFA data portfolio and not only individuals in 

an over-indebted situation. 

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In the 40-to-44 age 

group the percentage 

of defaulted loans in 

relation to all loans 

was around 2.4 percent 

in 2007. 

The percentage of defaulted loans stands around 2.5 percent 

Percentage of defaulted loans in relation to all loans by age group 

Percent 

Age group 

* Percentage of defaulted loans in relation to all loans for individuals (over 18 years old) 


Abb. 1.3 

After the amount of current loan obligations (chart 1.1) and the volumes of all standing and 

defaulted loans (chart 1.2) were presented, figure 1.3 documents the proportion of defaulted 

loans to all loans in the SCHUFA data portfolio between 2005 and 2007. This proportion in 

2007 initially rises for the age group of 25-to-29 year olds to 3.3 percent and then falls again 

in the remaining age groups. 

The amount of defaulted loans within the respective age groups nearly remained unchanged 

during the sample period. The overall average in 2007 was around 2.5 percent. Thus one can 

observe a slow growth rate since 2005 (when the percentage was 2.3 percent). 

Nevertheless, despite the very good economic situation in 2007 no clear general decline of loan 

defaults can be observed. Still it should be pointed out that the even the maximum percentage 

of defaulted loans in 2007 was only around 3.3 percent. On the other hand it means that nearly 

97 percent of all loans in the SCHUFA data portfolio were serviced in accordance with the terms 

of contract and without payment defaults.


The trend of first-time negative reports is dependent on the sector 

Chart 1.4, divided according to sector, shows which sector the first report of a payment default 

comes from. A first report will only be recorded once per individual, in either the telecommunications, 

banking or retail sector. It includes all first-time negative reports from companies affiliated 

with SCHUFA between 2005 and 2007. These affiliated companies passed on information on payment 

defaults (negative indicators) to SCHUFA, if sufficient reminder was given for a payable 

claim and it was not contested by the customer. 

It can be seen that in the young age group first negative reports come predominantly from the 

telecommunications sector. After that, first reports come increasingly from banks. The distribution 

of first reports consequently varies among the sectors. Whereas the first negative reports 

in banking rose up until to the middle age groups and then fell back after that, the values for 

the telecommunications sector went down from their peak among 20-to-24 year olds and then 

steadied in the later age groups. First negative reports in the retail sector shift at a relatively low 

level in comparison with the other sectors. 

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The most initial negative 

indicators of a payment 

default to a bank appear 

in the 40-to-44 age group. 

First-time payment defaults by sector 

Amount in thousands 



Age group 

2005 banking 

2006 banking 

2007 banking 

2005 retail 

2006 retail 

2007 retail 

2005 telecommunications 




Chart 1.4

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The percentage of 

individuals with at least 

one negative indicator 

averages at 10.6 percent 

for the 40-to-44 age 

group in 2007. 


Percentage of individuals with at least one negative indicator 

rose by 8.2 percent 

Percentage of individuals with at least one negative indicator 

in relation to all individuals in each age group 

Percent 

Age group 

* Percentage of individuals with at least one negative indicator in relation to all individuals (over 18 years old) 


Chart 1.5 

Chart 1.5 shows the percentage of individuals within each age group for whom there was at 

least one negative report in the SCHUFA data portfolio at the time of the survey. The percentage 

of individuals with at least one negative indicator in 2007 rises until it reaches the 25-to-29 year 

old age group and then continuously declines. 

In 2007 the average percentage of individuals with at least one negative indicator is around 

8.2 percent. The percentage of individuals with at least one negative indicator in the age group 

18-19 remains nearly constant between 2005 and 2007. In the remaining age groups, however, 

it rises slightly. 

While this evaluation does not distinguish between “soft” negative indicators (a payment default, 

for example) and “hard” negative indicators (such as the delivery of an oath of disclosure), the 

following figures show differentiated analyses of individuals with only soft negative indicators 

(chart 1.6) or with at least one hart negative indicator (chart 1.7). The differentiated analyses are 

important because over-indebtedness is seen in the research as a process that most often begins 

with a first payment default and can end with private insolvency as hard endpoint. 3 

3 Cf. Zimmermann, G.E.: Armut und Überschuldung, in: Debt Compass 2008, p. 143. 

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individuals with only 

soft negative indicators 

averages 4.6 percent 

for the age group 40-44 

in 2007. 

The percentage of individuals with only soft negative indicators 

is 3.9 percent 

The percentage of individuals with only soft negative indicators 

in relation to all individuals in the relevant age group 

Percent 

Age group 

* Percentage of individuals with only soft negative indicators in relation to all individuals (over 18 years old) 


Chart 1.6 

Following the evaluation of the percentage of individuals with at least one negative indicator 

(chart 1.5), figure 1.6 shows the percentage of individuals with only soft negative indicators. The 

next chart will show only the percentage of individuals with at least one hard negative indicator 

(chart 1.7). Soft negative indicators are payment defaults that are reported to SCHUFA, i.e. open 

uncontested bills receivable, where sufficient reminder was given, from companies associated 

with SCHUFA. 

These do not necessarily have to be equated with a risk of over-indebtedness or an over-indebted 

situation. Collectively, the percentage of individuals with soft negative indicators climbed from 

around 3.3 percent in 2005 to 3.9 percent in 2007. Figure 1.6 shows a trend similar to the one 

in figure 1.5. It is merely remarkable that in figure 1.5 the percentage of individuals with at least 

one negative indicator in the age group 20-to-24 remained nearly constant between 2005 and 

2007. As mentioned in figure 1.5, it is not possible to draw conclusions concerning the rate of 

over-indebtedness in each age group. However, outstanding debts or payment defaults can be 

the precursor to relative over-indebtedness.

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individuals with at least 

one hard negative 

indicator averaged 

6.0 percent in the age 

group 40 to 44 in 2007. 


The percentage of individuals with at least one hard negative indicator 

is 4.2 percent 

The percentage of individuals with at least one hard negative indicator 

in relation to all individuals in the relevant age group 

Percent 

Age group 

* Percentage of individuals with at least one hard negative indicator in relation to all individuals 

(over 18 years old) 


Chart 1.7 

Chart 1.7 shows the development of the percentage of individuals with at least one hard negative 

indicator in the SCHUFA data portfolio. Unlike a soft negative indicator (payment default), a 

hard negative indicator (such as the delivery of an oath of disclosure or the initiation of a private 

insolvency proceeding) can be assessed as a sign for an existing or imminent over-indebtedness 

situation. In contrast to the development of soft negative indicators (chart 1.6) it stands out here 

that the growth rate of individuals with hard negative indicators declined sharply between 2006 

and 2007 in nearly all age groups. This corresponds with the observation that private insolvency 

increased less keenly from 2006 to 2007 than it did from 2005 to 2006. 

Altogether, the average percentage of individuals with at least one hard negative indicator is 

4.2 percent. As in the previous year, the percentage of individuals with at least one hard negative 

indicator declined among 20-to-24 year olds. While another stagnation was apparent among 

25-to-29 year olds, there was a noticeable increase among 30-34 year olds: with a percentage of 

around 6.8 percent, they exhibit for the first time the highest percentage relative to all individuals 

with hard negative indicators. 

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Debt Compass | A | Sub-Analysis A-1 | 2 

30 

2. Regional Evaluations 

The evaluations on debt from chapter 1 will now be applied to a regional analysis by examining 

the German federal states (chart 2.1) and counties (map 2.1). 

The following chapter shows the regional distribution of individuals (over 18 years) with at least 

one negative indicator. The tabular breakdown (chart 2.1) shows the federal state level, while 

the map of Germany (map 2.1.) depicts the analysis on county level. 

The distinction between federal state and county level is revealing, because the distribution of 

individuals with negative indicators within a federal state often gives a very differentiated picture.

i 

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In the federal state of 

Hessen, the percentage 

of individuals with at 

least one negative indicator 

was 7.9 percent in 2007. 

On the national level, 

8.2 percent have at least 

one negative indicator. 


The percentage of individuals with at least one negative indicator 

of all individuals (over 18 years) in the respective federal state, 2007 

Bavaria 

Baden-Württemberg 

Saxony 

Thuringia 

Hesse 

Rhineland Palatinate 

Lower Saxony 

Brandenburg 

Schleswig-Holstein 

Saarland 

Mecklenburg Western Pomerania 

Saxony-Anhalt 

Hamburg 

Northrhine-Westphalia 

Bremen 

Berlin 

Percent 

* Percentage of individuals (over 18 years) with at least one negative indicator 

for Germany 


Chart 2.1 

Total = 8.2* 

Examining the individual 429 counties (map 2.1) in more detail shows that the percentage of 

individuals with at least one negative indicator varies from region to region. While in Northrhine- 

Westphalia (NRW) an average of 9.4 individuals shows at least one negative indicator, the individual 

NRW counties also have percentages of below four percent or above ten percent. This 

shows that although the percentage of individuals with one negative indicator is above average 

on federal state level, there are counties in Northrhine-Westphalia that are significantly below the 

national average. Similar differences can be seen on the map of Germany for other counties as 

well. In Bayern and Baden-Württemberg, the percentage of individuals with one national indicator 

is significantly below the overall national average. But in these states, too, there are counties 

where the percentage of individuals with at least one negative indicator is above ten percent. 

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The graduation of colours 

from light to dark signifies 

an increase in percentage, 

i.e. the darker the county, 

the higher the percentage 

of individuals with at least 

one negative indicator. 

The percentage of individuals with at least one negative indicator 

of all individuals (over 18 years) in the respective county, 2007 

Percent 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 


Map 2.1 

SAARLAND 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 

SAXONY- SAXONY- 

ANHALT ANHALT 

THURINGIA 

MECKLENBURG 

WESTERN WESTERN 

POMERANIA 

POMERANIA 

BAVARIA BAVARIA 

BERLIN 

BRANDENBURG 

SAXONY

3. Risk Model 


The SCHUFA risk model, first developed for the 2004 Debt Compass, classified levels of debt 

into four different risk groups. An indicator model makes possible analyses about, for example, 

the course over-indebtedness takes. 

The risk groups are organized into green, yellow, orange and red levels. In the green risk level, 

there are no indications of payment difficulty. Individuals with payment difficulties relating to 

the mail order, e-commerce or telecommunications sectors count toward the yellow risk level. 

In the orange risk level, on the other hand, are bank loan payment defaults. The red risk level is 

for individuals who show signs of a critical financial situation which can be classified as absolute 

over-indebtedness. Indications of this are, e.g., the delivery of an oath of disclosure or information 

about consumer insolvency proceedings. 

The indicators included in the risk model are presented on the following page. 

Possible analyses of the risk model 

In addition to the evaluation of all adult individuals, there is a separate evaluation of the 18 to 24 

year old age group. 

With the study of mobility between the different risk levels, it is possible to present whether there 

is a way out of over-indebtedness or the threat of over-indebtedness. For this purpose, the period 

from 2002 to 2007 will be examined (cf. chapter 3). 

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34 

3.1 Risk model and indicators of the risk levels 

The following indicators are included in the risk levels: 

• No negative indicators and no current credit obligation of any kind 

• No negative indicator and current credit obligation with a SCHUFA default rate 

according to a score < 10 percent 

The default rate indicates for the evaluated group of individuals the percentage of individuals 

within the rating level who have received a negative status after a defined time period of 

15 months. 

• Only discharged negative indicators 

• No negative indicator and current credit obligation and SCHUFA default rate according 

to a score > 10 % 

• One current negative indicator only from the non-banking sector 

• More than one current negative indicator from the non-banking sector 

The so-called non-banking sectors are the following: 

Retail, mail order, e-commerce, telecommunications, etc. 

• Unsettled negative indicator from a bank, less than 1 year ago 

• Unsettled negative indicator from a bank, less than 1 year ago, and also from 

a non-banking sector 

• Unsettled negative indicators from at least one bank from less than 1 year ago 

• Negative indicator history at least one bank within 1 to 3 years of the study 

Unsettled negative indicators are payment defaults, i.e. uncontested, sufficiently 

reminded claims not yet settled by payment. 

• Indicator of oath of disclosure (EV = Eidestattliche Versicherung) or arrest order for the delivery 

of an oath of disclosure 

• Indicator of personal insolvency 

• Individuals with search mandate 

Search mandate means that a client of SCHUFA owns a claim that is unsettled, sufficiently 

reminded and uncontested against a customer who has moved without a forwarding address.

Number of individuals in the risk levels 


The total SCHUFA data portfolio of approx. 65 million native adults in Germany was made 

anonymous and analysed for the Debt Compass. With the help of risk models, a differentiated 

allocation of all individuals into the different risk levels is possible. Table 3.1.1 shows how many 

individuals at least 18 years old are found in which risk level. Young adults, between 18 to 24 

years old, are separately considered in Table 3.1.2. 

Individuals in the 2007 risk levels 

Warning level Number Percentage (2007) Percentage (2006) 

• Green 58,624,219 89.9 90.0 

• Yellow 2,341,536 3.6 3.3 

• Orange 1,019,946 1.5 1.6 

• Red 3,265,514 5.0 5.1 

Total 65,269,215 100.0 100.0 

Tab. 3.1.1 

Individuals between 18 and 24 years old in the 2007 risk levels 

Warning level Number Percentage (2007) Percentage (2006) 

• Green 5,231,336 86.4 86.5 

• Yellow 533,744 8.8 8.4 

• Orange 59,406 1.0 1.0 

• Red 229,310 3.8 4.1 

Total 6.053,796 100.0 100.0 

Tab. 3.1.2 

Around 90 percent of all individuals whose information is stored by SCHUFA are in the green 

risk level. The percentage of all adults in the red level rose by around five percent from 2006. 

However, the differentiated examination of individuals between 18 and 24 years old shows 

a decline in the percentage of young adults in this risk level: from 4.1 percent in 2006 to 

3.8 percent in 2007. 

Since the process of over-indebtedness begins before reaching one of the hard negative indicators 

(red level), the yellow and orange warning levels are especially important. The percentage 

of 18 to 24 year olds is in contrast to that of all age groups in the yellow level, with nearly nine 

percentage points over the average of about 3.6 percent. However, the percentage of young 

adults in the orange level is around one percent, while the general average is around 1.5 percent. 

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An overwhelming 

percentage of individuals 

(94.8 %) who were in 

the green level in 2002 

still have no negative 

indicators five years later, 

and so are placed in 

the green level. 

3.2 Development of risk levels between 2002 and 2007 

For the assessment of private debt and over-indebtedness, it is of central importance whether the 

critical financial situations previously intensified, or whether there is a way out of over-indebtedness 

or the risk of over-indebtedness. Figures 3.2.1 and 3.2.2 examine the mobility between the 

different debt levels (green, yellow, orange and red) over a five-year period. As in the previous 

examinations, data will be separated between all adult individuals (chart 3.2.1) and young adults 

between 18 and 24 (chart 3.2.2). 

Change in the risk levels for all individuals in the entire data portfolio 

from 2002 to 2007 

Percent 

green 

yellow 

orange 

red 


Chart 3.2.1 

green yellow orange red 

The study of all adults registered in the data portfolio (chart 3.2.1) shows that of the individuals 

who were in the green sector in 2002, 94.8 percent were still in the same group five years later. 

Only a small percentage (1.9 %) switched to the red, or critical, sector. At the same time it can 

be seen that more than half (56.9 %) of the individuals who were in the red group in 2002 are 

still in the red group. A different conclusion can be drawn from the fact that about a quarter of 

the individuals have made the jump to the green group. 

The transition levels, yellow and orange, display the greatest mobility. Five years later, the majority 

of individuals who used to be in the yellow risk level now have no acute indicators of being 

threatened by over-indebtedness. The development in the orange sector presents itself differently: 

here the largest portion has not fundamentally improved their financial situation, and indeed 

for about a fourth it has worsened into the red level, a situation of concrete over-indebtedness. 

This is, for example, a consumer insolvency proceeding or the delivery of an oath of disclosure.

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18.9 percent of all 

18 to 24 year olds who 

wereconfronted with 

a situation of critical 

indebtedness or overindebtedness 

in 2002 

(red level) were able to 

reach the green level. 


Change in the risk levels for young adults (ages 18-24)* from 2002 to 2007 

Percent 

green 

yellow 

orange 

red 


Chart 3.2.2 

green yellow orange red 

* Most of these individuals are no longer in the 18-24 age group in 2007 

The study of young adults (18 to 24 years old, chart 3.2.2) shows that critical financial situations 

are not necessarily self-reinforcing, even among the younger age groups. Between 2002 and 

2007 almost half of 18 to 24 year olds were able to move out of the critical red level. 

An overwhelming majority of young adults (88.6 %) who had no negative indicators registered 

with SCHUFA in 2002 and thus were in the green risk level, also have no information of noncontractual 

behaviour five years later. At the same time, more than half of the young adults who 

were in the red level in 2002 have not left this critical situation by 2007. Furthermore it can be 

seen that young adults previously in the orange level have more quickly arrived in the critical red 

risk level than the older age groups. Nevertheless, the percentage of young adults in the orange 

group is negligible, with around one percent in 2007 (cf. table 3.1.2). Altogether, both studies 

show that the majority of individuals who were in the green level at the beginning of the study 

period were still presenting no information about payment defaults five years later. In the same 

period around a fourth of people who found themselves in a critical situation of indebtedness or 

over-indebtedness in 2002 saw their financial position stabilize and were able to reach the green 

level. 

Since development is fairly dynamic, critical financial situations do not always intensify and there 

are ways out of even a critical financial situation; nevertheless, the evaluations show a rather 

strong mobility toward the red level. There is a higher probability of moving into the red group 

from the yellow or orange levels than there is from the green level. 

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38 

3.3 Regional view of risk levels – all private individuals 

The following two chapters show the regional occurrence, by county, of each risk level by means 

of maps of the Federal Republic of Germany. As in the preceding chapters, there will be a distinction 

made here between all individuals recorded in the SCHUFA data portfolio, and young adults. 

Chapter 3.3 (maps 3.3.1 through 3.3.4) gives information about the percentage of individuals 

reported to SCHUFA in each respective risk level in 2007. The first to be considered are all 

individuals over 18 years old who were recorded in the SCHUFA data portfolio, in the respective 

counties. 

Chapter 3.4 (maps 3.4.1 through 3.4.4) evaluates regional risk levels among young adults 

between 18 and 24 in 2007. Divided into the green, yellow, orange and red groups, the various 

maps of Germany show the percentage of 18 to 24 year olds in each risk group out of all young 

adults in the respective counties.

i 

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The darker the county, 

the more people in 

the green risk level 

(cf. p. 34 for explanation). 

The trend is that individuals 

living in the south are 

more likely to be at levels 

with the least risk. 

Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.3.1 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 


Percentage of individuals from the green group out of all individuals 

(over 18 years old) in the respective county, 2007 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY 

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of individuals in the 

yellow risk group 

(cf. page 34 for explanation). 

Percentage of individuals from the yellow group out of all individuals 


Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.3.2 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY

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of individuals in the 

orange risk group 



Percentage of individuals from the orange group out of all individuals 

(over 18 years old) in the respective county, 2007. 

Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.3.3 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY 

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of individuals in the red 

risk group (cf. page 34 for 

explanation). 

Percentage of individuals from the red group out of all individuals 


Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.3.4 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY


3.4 Regional view of risk levels – young adults 

While the previous chapters (maps 3.3.1 through 3.3.4) presented the regional occurrence of the 

percentage of all individuals over 18 years old in the contained in the SCHUFA data portfolio, the 

following maps of Germany (3.4.1 through 3.4.4) only account for young adults between 18 and 

24 years old. 

Divided into green, yellow, orange and red risk levels, the various maps of Germany show for 

2007 the percentage of 18 to 24 year olds out of all young adults in the respective county and 

the respective risk level. 

For the regional view of risk levels among young adults, it should be borne in mind that a 

pre-dominant number of people under 25 years old still reside in the household of their parents. 

An external analysis showed that about 99 percent of 18 to 19 year olds and approx. 61 percent 

of 20 to 24 year olds still live with their parents. 4 Therefore, let it be noted for the red level 

in particular that it does not always amount to an actual over-indebted situation. Many 18 to 24 

year olds are still likely to have the financial resources of the household at their disposal. 

Although not all young adults in the orange and red risk levels find themselves directly in overindebtedness 

or at risk of over-indebtedness, nevertheless it is critical to assess entrance into one 

of these levels against the background of a potential “over-indebtedness career”. 

4 Zimmermann, G.E.: Sozialprofile ver- und überschuldeter Personen, Auswertungen auf Basis des 

Sozio-oekonomischen Panel (SOEP), [Social profile of indebted and over-indebted individuals, 

evaluation on the basis of Socio-economic Panel (SOEP) data] in: SCHUFA holding company (ed.), 

Debt Compass 2005, Wiesbaden 2005, p. 144. 

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the more young adults 

who are in the green risk 

group (cf. page 34 for 

explanation). The trend is 

that individuals living 

in the south are more 

likely to be at levels with 

the least risk. 

Percentage of young adults (age 18-24) from the green group 

out of all young adults, 2007 

Percent 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 


Map 3.4.1 

SAARLAND 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY

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of young adults who 

are in the yellow risk group 



Percentage of young adults (age 18-24) from the yellow group 


Percent 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 


Map 3.4.2 

SAARLAND 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY 

Please note: The regional risk levels for young adults generally have the same grading as that chosen for 

the risk levels of all individuals. It is only in the case of the yellow level that a different grading has been 

chosen for young adults because all counties show a percentage point of more than 3.5 percent. If one 

were to keep the grading used to evaluate all individuals, this would result in a uniform coloration without 

any declaratory power. 

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of young adults who are 

in the orange risk group 


Percentage of young adults (age 18-24) from the orange group 


Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.4.3 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY

i 

Reader help: 



of young adults who are 

in the red risk group 


Percentage of young adults (age 18-24) from the red group 


Percent 

RHINELAND 

PALATINATE 

SAARLAND 

NORTHRHINE- 

WESTPHALIA 


Map 3.4.4 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 


HAMBURG 


ANHALT ANHALT 

THURINGIA 

MECKLENBURG 


POMERANIA 

POMERANIA 


BERLIN 

BRANDENBURG 

SAXONY 

47

Debt Compass | A | Sub-Analysis A-2 | Contents 

Analysis A: 

Representative Evaluation of the SCHUFA Data 


Sub-Analysis A-2: Private Debt Index (PDI) 

1. Private Debt Idex 51 


2.1 Evaluation by federal state 

2.2 Evaluation by county 

2.3 Evaluation of cities 

3. Forecast 2009 61 

3.1 Forecast on federal state and county level 

4. Tabular overviews 

– Overview: Private Debt Index (PDI) in the federal states 

– Overview: Private Debt Index (PDI) in the counties 

64 

49


50 

Introduction 

The Private Debt Index (PDI), which was developed by SCHUFA, is an instrument that not only 

analyses the historical development of critical indicators for private debt, but also forecasts the 

future development in the medium range. 

The forecasts of the PDI are unique in over-indebtedness research, because a single index figure 

from a wealth of individual indicators shows the private debt and over-indebtedness situation in 

all Germany, the 16 federal states and the currently 429 counties. 

The PDI shows the extent to which the risk of over-indebtedness has decreased or increased, and 

how strong the critical indicators for private debt are represented in the individual geographical 

regions. To show the considerably varying regional development of private debt, the PDI figures 

for the five largest German cities are presented on zip code level in addition to the analyses on 

national and county level. 

The full year forecast has made the PDI the most important barometer for critical indicators 

of private debt in Germany. This increases transparency with respect to the over-indebtedness 

situation or over-indebtedness risk of private individuals in Germany. In view of tight money 

markets at present, the PDI can serve as an early warning signal that is important for the German 

economy. 

www.privatverschuldungsindex.de 

The current analyses are based on actual data from SCHUFA’s total data portfolio (reporting date 

30 June 2008), as well as on the change as compared to the preceding year 2007 (reporting date 

31 December 2007) and the predicted changes for 2009 (reporting date 31 December 2009). 

The following chapters present the results of the PDI. Further analyses with the PDI in combination 

with further trends of debt and over-indebtedness with an interactive map of Germany are 

available in the internet at: www.privatverschuldungsindex.de

1. Private Debt Index 


To show the different degrees of private over-indebtedness risk, the PDI takes into account 

a number of measurable indicators of private debt and over-indebtedness. The data is based 

on credit relevant information of SCHUFA Holding AG on around 65 million private adult individuals 

in Germany. 

Due to the varying situation of private debt or over-indebtedness risk in the individual regions 

of Germany, the PDI does not only provide a figure for all Germany, but additionally serves as a 

yardstick for the 16 federal states and the currently 429 counties in Germany. The Index figures 

for the federal states and counties – divided into the levels green, yellow, orange and red – are 

depicted with the help of a cluster analysis. Moreover, the PDI is calculated for the zip code are 

as by means of examples for the five largest German cities. 

The levels of the PDI 

The PDI figures are divided into four degree levels. Accordingly, the critical indicators 

of debt risk can be 

• slight 

• moderate 

• strong 

• very strong 

The individual federal states, counties and cities are allocated to the respective sectors in accordance 

with a defined weighting using the defining indicators of the three risk levels (yellow, 

orange, red) of the risk model (cf. analysis A-1, chapter 3). As the green level of the risk model 

does not take into account negative indicators, it is not included in the Index calculation. 

Consequently, it has to be noted that the colour classification should not be confused with 

the allocation of the risk levels from the risk model. 

Components of the PDI 

In order to calculate the PDI, a combination of negative relevant information for the respective 

residential population was studied and weighted individually, and an overall figure was calculated. 

Below, the so-called soft and hard negative indicators are listed, which served to calculate the 

PDI. These soft and hard negative indicators are divided into the three levels yellow, orange and 

red depending on their degree. 

51


52 

The soft negative indicators (yellow and orange level) are payment defaults at non-banks and 

banks. The red level includes hard negative indicators such as information on the delivery of an 

oath of disclosure or personal insolvency proceedings. The indicators on the red level can be 

evaluated as a clear sign of the threat or occurrence of an over-indebted situation. The indicators 

on the red risk level were weighted most strongly for the calculation of the PDI to be able to 

sharply filter out the regions with the critical private debt. 

Yellow level 

• Only discharged negative indicators 

• No negative indicator and current credit obligation and SCHUFA default rate according 

to a score > 10 percent 

• One current negative indicator only in the non-banking sector 

• More than one current negative indicator in the non-banking sector 

The so-called non-banks are the following sectors: 

Retail, mail order, e-commerce, telecommunications, etc. 

Orange level 

• Unsettled negative indicator from a bank newer than 1 year 

• Unsettled negative indicator from a bank newer than 1 year and from non-banks 

• Unsettled negative indicators from at least one bank newer than 1 year 

• Negative indicator history from at least one bank of 1 to 3 years 

Unsettled negative indicators are payment incidents, i.e. unpaid, sufficiently dunned and 

uncontested claims not yet settled by payment. 

Red level 

• Indicator oath of disclosure (EV = Eidestattliche Versicherung) or arrest order for the delivery 

of an oath of disclosure 

• Indicator of personal insolvency 

• Individuals with search mandate 

Search mandate means that a client of SCHUFA owns an unsettled, sufficiently reminded 

and uncontested claim against a customer who has moved without a forwarding address.

2. Regional Evaluations 


Below, the Private Debt Index (PDI) is used to show the degree to which critical indicators of 

private debt are present in the various regions in Germany. While the maps 2.1 and 2.2 depict 

the evaluation on the level of federal states and counties (cf. tabular overviews in chap. 4), the 

indicators for private debt are also shown with the help of an analysis on the level of zip codes 

for the five largest German cities (maps 2.3.1 – 2.3.5) The following chapter 3 includes the 

predicted change of the critical indicators as at 31 December 2009. 

Overall, the Private Debt Index was 1,149 for all Germany in 2008 (reporting date 30 June 2008). 

The PDI figure has thus hardly changed compared with the preceding year (2007: 1,147). But 

in comparison to the national Index figure, regional changes of the PDI give a very differentiated 

picture. 

Evaluation on federal state level 

Overall, the Index figures of five federal states have slightly decreased since 2007 and thus have 

shown a reduction of critical indicators of private debt and over-indebtedness. With the exceptions 

of the federal states of Rhineland-Palatinate, Hamburg and Saxony-Anhalt, where the PDI 

figure did not change, in the eight other federal states an increase in the critical indicators of 

private debt can be seen to emerge. The growth rates in these eight federal states, however, 

vary considerably. While comparatively high growth can be seen in Brandenburg, Northrhine- 

Westphalia and Saarland, the other federal states have only shown a very low PDI growth since 

2007 (see tabular overviews in chap.4). As in preceding years, the tendency for a discrepancy 

between the north and south can be seen in the current evaluations as well, with the degrees 

of the Index within a state varying considerably. 

Evaluation on county level 

Similar to the findings of the preceding year, the evaluation on county level shows the continuously 

dynamic development of private debt situations. The results partly show significant 

increase or decrease of the Index figure in the individual counties (see tabular overview in 

chap. 4). Generally, an examination of all 429 counties does not indicate a region where the 

critical indicators regarding over-indebtedness are highly concentrated. The counties with 

a high degree of critical indicators for private debt are distributed across the entire country. 

Evaluation of five cities 

The evaluation of Germany’s five largest cities (Berlin, Hamburg, Munich, Cologne, Frankfurt) 

confirms the general trend as found on national and county level. The more differentiated the 

regional evaluation of critical indicators of private debt, the more varying are critical indicators 

distributed. The city maps (see maps 2.3.1 - 2.3.5) show, that – despite a medium to high overindebtedness 

risk on federal state and county level – an evaluation on zip code level leads to 

areas in the individual cities with only a low degree of critical indicators. 

53


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Reader help: 

The PDI describes the degree 

of critical indicators of debt. 

The colour green means 

that there are critical indicators 

only to a low extent. 

Red, however, signifies a 

significant degree of critical 

indicators. 

2.1 Evaluation by federal state 

Critical indicators of private debt according 

to the Private Debt Index (PDI), first half of 2008, federal states 

characteristics 

minor 

moderate 

significant 

extreme 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 

SAARLAND 

BREMEN 


Map 2.1 

SCHLESWIG- 

HOLSTEIN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

MECKLENBURG 

HAMBURG WESTERN 

POMERANIA 

SAXONY- 

ANHALT 

THURINGIA 

BAVARIA 

BERLIN 

BRANDENBURG 

SAXONY

i 

Reader help: 

The PDI describes the 

degree of critical indicators 

of debt. The colour green 

means that there are critical 

indicators only to a limited 

degree. Red, however, 

signifies a significant 

degree of critical indicators. 

2.2 Evaluation by county 

Critical indicators of private debt according 

to the Private Debt Index (PDI), first half of 2008, counties 


minor 

moderate 

significant 

extreme 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 

SAARLAND 

BREMEN 


Map 2.2 

SCHLESWIG- 

HOLSTEIN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 


MECKLENBURG 


POMERANIA 

SAXONY- 

ANHALT 

THURINGIA 

BAVARIA 

BERLIN 

BRANDENBURG 

SAXONY 

55


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2.3 Evaluation of cities 

PDI/Berlin 


slight 

moderate 

strong 

very strong 

Spandau 

Reinickendorf 

CharlottenburgWilmersdorf 

Steglitz- 

Zehlendorf 


Map 2.3.1 

Pankow 

Centre 

Friedrichshain 

Kreuzberg 

Tempelhof 

Schöneberg 

Neukölln 

Lichtenberg 

Marzahn 

Hellersdorf 

Treptow- 

Köpenick

i 

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PDI/Hamburg 


slight 

moderate 

strong 

very strong 

Altona 

Eimsbüttel 

Harburg 


Map 2.3.2 

North 

Centre 


Wandsbeck 

Bergedorf 

57


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signifies significant degree 

of critical indicators. 

PDI/Munich 


slight 

moderate 

strong 

very strong 

Aubing- 

Lochhausen- 

Langwied 

1 Altstadt – Lehel 

2 Ludwigsvorstadt – Isarvorstadt 

3 Maxvorstadt 

4 Schwanthalerhöhe 

5 Au – Haidhausen 

Allach- 

Untermenzing 

Feldmoching- 

Schwabing- 

Hasenbergl 

Freimann 

Milbertshofen- 

Am Hart 

Moosach 

Schwabing- 

Pasing- 

Neuhausen- West 

Ober- 

Nymphenburg 

menzing 

3 

1 

Laim 4 

Hadern 


Map 2.3.3 

Thalkirchen 

Obersendling 

Forstenried 

Fürstenried 

Solln 

Sendling-SendWestlingpark 

Bogenhausen 

Berg am 

Laim 

2 

5 

Ober- 

Trudering- 

Riem 

giesingUnterRamersdorfgiesing 

Perlach 

Harlaching

i 

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PDI/Cologne 


slight 

moderate 

strong 

very strong 

Chorweiler 

Ehrenfeld 

Lindenthal 


Map 2.3.4 

Nippes 

City Centre 

Rodenkirchen 


Mülheim 

Kalk 

Porz 

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PDI/Frankfurt 


slight 

moderate 

strong 

very strong 

West 


Map 2.3.5 

Kalbach 

Centre- 

West 

Nieder- 

Eschbach 

Centre- 

North 

City Centre 

Nieder- 

Erlenbach 

Harheim 

Northwest Northeast 

East 

South 

Bergen- 

Enkheim

3. Forecast 2009 


The following section presents the forecasts of the Private Debt Index for the period from the 

end of 2008 until the end of 2009. With the forecast, the PDI does not only show the historical, 

but also the long-term, future development of critical indicators of private debt. That makes the 

PDI a unique instrument for the monitoring of private debt and over-indebtedness trends. Tabular 

overviews in chapter 4 show the forecasts as well as the changes as compared to the calculated 

actual figures. 

In the current forecast period until 31 December 2009, the forecast for all Germany shows 

stagnation on the level of the preceding years. While in past the increase of the PDI was 

slowed down, such a development is not to be expected according to the current forecast. 

3.1 Forecast on federal state and county level 

Compared to the national development, the predicted changes on county level vary considerably. 

A PDI increase and thus an increase of critical indicators is forecast for eight federal states from 

the end of 2008 until the end of 2009. Only in Thüringen, these over-indebtedness risks neither 

increase nor decrease. 

On county level, the prognosis until the end of 2009 shows a PDI decrease for 186 of 429 counties. 

The forecast predicts a PDI increase for 218 counties – around half of them – and neither an 

increase or a decrease for 25 counties (change actually smaller +0.1 %). 

61


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Reader help: 

The map shows the predicted 

change in critical 

indicators of private debt 

as of 31 December 2009. 

The green colour, for example, 

indicates that critical 

indicators will decrease. 

Predicted change in critical indicators of private debt according to the 

Private Debt Index (PDI), from the first half of 2008 until the end of 

2009, federal states 

pred. change PDI 

decrease 

constant 

increase 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 

SAARLAND 

BREMEN 


Map 3.1.1 

SCHLESWIG- 

HOLSTEIN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

MECKLENBURG 


POMERANIA 

SAXONY- 

ANHALT 

THURINGIA 

BAVARIA 

BERLIN 

BRANDENBURG 

SAXONY

i 

Reader help: 

The map shows the predicted 

change in critical 

indicators of private debt 

as of 31 December 2009. 

The green colour, for example, 

indicates that critical 

indicators will decrease. 

pred. change PDI 

decrease 

constant 

increase 


Map 3.1.2 


Predicted change in critical indicators of private debt according to the Private 

Debt Index (PDI), from the first half of 2008 until the end of 2009, counties 

RHINELAND 

PALATINATE 

NORTHRHINE- 

WESTPHALIA 

SAARLAND 

SCHLESWIG- 

HOLSTEIN 

BREMEN 

LOWER SAXONY 

HESSE 

BADEN- 

WÜRTTEMBERG 

MECKLENBURG 


POMERANIA 

SAXONY- 

ANHALT 

THURINGIA 

BAVARIA 

BERLIN 

BRANDENBURG 

SAXONY 

63


64 

4. Tabular Overviews 

The following tabular overviews show the PDI figures for 2008 (reporting date 30 June 2008) 

and 2007 (reporting date 31 December 2007) for the federal states (tab. 4.1) and the currently 

429 counties and municipalities (tab. 4.2) with the correspondingly calculated Private Debt Index 

(PDI). In addition, the tables include the respective forecast for 2009 (reporting date 31 December 

2009). 

Depending on the level of the Index figure, a federal state or a county is in the green, yellow, 

orange or red level. In the regions with the lowest Index figure, the critical indicators for 

private debt are most weakly represented. In the tables, these regions occupy the top places. 

Generally, the developments of PDI figures vary more significantly on county level than on 

federal level. 

Reader help 

The tables are to be read as follows: If the Index for federal state A is, for example, 1,000 

points and for federal state B, for example, 1,200 points, it means that the critical indicators 

of private debt in federal state B are 20 percent more strongly represented than in federal 

state A. The same applies to the figures for the counties. 

Apart from the list of the respective PDI figures, the tabular overviews include the changes of 

the PDI figures from 2007 to 2008 and from 2008 to 2009. 

A change in a county of plus 2.10 percent from 2007 to 2008, for instance, means that the PDI 

has increased by 2.10 percent from 2007 to 2008 and thus the critical indicators for private debt 

have increased by 2.10 percent. 

A change with a negative sign signifies a decrease in the Index figure and a decrease in critical 

indicators for private debt.

Ranking: Private Debt Index (PDI) in the Federal States 

Rank 

2008 

First half** 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

10 

12 

13 

14 

15 

16 

Federal state 

Baden-Württemberg 

Bavaria 

Hesse 

Saxony 

Rhineland Palatinate 

Thuringia 

Hamburg 

Brandenburg 

Schleswig-Holstein 

Lower Saxony 

Northrhine-Westphalia 

Saarland 

Mecklenburg Western Pomerania 

Saxony-Anhalt 

Bremen 

Berlin 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

812 

839 

963 

984 

1015 

1025 

1029 

1090 

1130 

1136 

1141 

1143 

1225 

1228 

1252 

1462 

1149 

Change 

2007*/2008 

[%] 

-0,37 

-0,71 

0,10 

0,72 

0,00 

-0,29 

0,00 

1,11 

0,36 

0,35 

1,06 

1,78 

-0,41 

0,00 

0,16 

-0,41 

0,17 

Rank 

2007* 

1 

2 

3 

4 

5 

6 

7 

8 

10 

12 

11 

9 

14 

13 

15 

16 


PDI 

2007* 

815 

845 

962 

977 

1015 

1028 

1029 

1078 

1126 

1132 

1129 

1123 

1230 

1228 

1250 

1468 

1147 

Rank 

2009* 

pred. 

1 

2 

3 

4 

6 

7 

5 

8 

9 

10 

11 

12 

13 

14 

15 

16 

PVI 

2009* 

pred. 

808 

828 

962 

994 

1017 

1025 

1014 

1099 

1131 

1139 

1153 

1155 

1218 

1227 

1260 

1454 

1148 

Change 

2008/2009* 

pred. [%] 

Tab. 4.1 *Reporting date 31 Dec. of the respective year / **reporting date 30 June of the respective year 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

-0,49 

-1,31 

-0,10 

1,02 

0,20 

0,00 

-1,46 

0,83 

0,09 

0,26 

1,05 

1,05 

-0,57 

-0,08 

0,64 

-0,55 

-0,09 

65


Ranking: Private Debt Index (PDI) in the Counties 

66 

Rank 


First half** 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

15 

17 

18 

19 

20 

21 

22 

22 

24 

24 

26 

27 

28 

28 

30 

31 

32 

33 

34 

35 

36 

37 

38 

38 

Name 

Eichstätt, county 

München, county 

Starnberg, county 

Ebersberg, county 

Erlangen-Höchstadt, municipality 

Heidelberg, county 

Tübingen, county 

Main-Taunus county 

Jena, municipality 

Hochtaunus county 

Fürstenfeldbruck, county 

Böblingen, county 

Roth, county 

Rosenheim, county 

Dachau, county 

Fürth, county 

Biberach, county 

Main-Tauber county 

Alb-Donau county 

Stollberg, county 

Esslingen, county 

Augsburg, county 

Trier-Saarburg, county 

Ravensburg, county 

Schweinfurt, county 

Niederschlesischer Oberlausitz, c. 

Rheingau-Taunus county 

Aichach-Friedberg, county 

Bodensee county 

Würzburg, county 

Traunstein, county 

Reutlingen, county 

Bad Tölz-Wolfratshausen, county 

Erlangen, municipality 

Heilbronn, county 

Regensburg, county 

Freising, county 

Freudenstadt, county 

Neuburg-Schrobenhausen, county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

534 

539 

546 

553 

577 

582 

593 

605 

617 

632 

637 

648 

651 

657 

659 

659 

662 

664 

666 

668 

669 

670 

670 

674 

674 

676 

677 

679 

679 

692 

697 

699 

706 

712 

715 

718 

720 

724 

724 

1149 

Change 


[%] 

-0,56 

0,75 

-1,80 

0,00 

-0,17 

-1,69 

0,85 

1,85 

-1,12 

0,64 

0,95 

1,09 

-1,96 

1,86 

0,61 

-0,60 

-0,45 

-2,35 

-2,49 

-0,30 

0,00 

-1,47 

-0,15 

0,75 

-0,44 

0,30 

0,00 

-1,02 

0,00 

0,29 

0,72 

-1,27 

0,28 

-2,20 

0,28 

-0,14 

0,14 

-2,03 

-9,95 

0,17 

Rank 

2007* 

2 

1 

4 

3 

5 

7 

6 

8 

9 

10 

11 

12 

16 

13 

14 

15 

17 

26 

28 

20 

18 

26 

21 

18 

23 

22 

23 

29 

25 

30 

31 

33 

32 

37 

34 

35 

35 

40 

76 

PDI 

2007* 

537 

535 

556 

553 

578 

592 

588 

594 

624 

628 

631 

641 

664 

645 

655 

663 

665 

680 

683 

670 

669 

680 

671 

669 

677 

674 

677 

686 

679 

690 

692 

708 

704 

728 

713 

719 

719 

739 

804 

1147 

Rank 

2009* 

pred. 

5 

2 

1 

4 

7 

6 

8 

11 

10 

13 

16 

18 

21 

23 

23 

17 

19 

14 

12 

26 

27 

15 

21 

29 

23 

33 

27 

31 

30 

37 

39 

34 

36 

35 

43 

42 

40 

41 

9 

PDI 

2009* 

pred. 

551 

536 

523 

542 

575 

573 

602 

618 

610 

634 

650 

653 

661 

668 

668 

651 

657 

644 

633 

671 

672 

648 

661 

674 

668 

687 

672 

684 

681 

701 

702 

692 

698 

696 

717 

714 

708 

710 

607 

1148 

Change 


pred. [%] 

3,18 

-0,56 

-4,21 

-1,99 

-0,35 

-1,55 

1,52 

2,15 

-1,13 

0,32 

2,04 

0,77 

1,54 

1,67 

1,37 

-1,21 

-0,76 

-3,01 

-4,95 

0,45 

0,45 

-3,28 

-1,34 

0,00 

-0,89 

1,63 

-0,74 

0,74 

0,29 

1,30 

0,72 

-1,00 

-1,13 

-2,25 

0,28 

-0,56 

-1,67 

-1,93 

-16,16 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

-0,09


Rank 


First half** 

40 

41 

42 

43 

44 

44 

46 

47 

48 

49 

50 

50 

52 

53 

54 

55 

56 

56 

56 

59 

60 

61 

61 

61 

64 

65 

66 

67 

68 

69 

70 

71 

71 

73 

74 

75 

76 

77 

77 

Name 

Rottweil, county 

Amberg-Sulzbach, county 

Neustadt a.d.Waldnaab, county 

Rhein-Pfalz county 

Donau-Ries, county 

Main-Spessart, county 

Hohenlohe county 

Landsberg am Lech, county 

Stormarn, county 

Miesbach, county 

Enz county 

Pfaffenhofen a.d.Ilm, county 

Unterallgäu, county 

Rhein-Neckar county 

Erding, county 

Ludwigsburg, county 

Harburg, county 

Mittlerer Erzgebirgs county 

München, municipality 

Münster, municipality 

Aschaffenburg, county 

Bamberg, county 

Karlsruhe, county 

Neumarkt i.d.OPf., county 

Kamenz, county 

Breisgau-Hochschwarzwald, county 

Weißeritz county 

Rastatt, county 

Ansbach, county 

Eichsfeld, county 

Rottal-Inn, county 

Altötting, county 

Berchtesgadener Land, county 

Mainz, municipality 

Weilheim-Schongau, county 

Rhein-Hunsrück county 

Lindau (Bodensee), county 

Neu-Ulm, county 

Rems-Murr county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

725 

726 

730 

739 

740 

740 

741 

748 

755 

756 

759 

759 

761 

764 

765 

766 

767 

767 

767 

769 

776 

777 

777 

777 

778 

779 

780 

781 

787 

789 

790 

792 

792 

795 

797 

799 

802 

803 

803 

1149 

Change 


[%] 

-2,03 

-6,08 

-4,70 

0,27 

-1,60 

-2,25 

0,68 

0,94 

1,48 

-1,05 

1,07 

-1,17 

2,98 

0,00 

2,14 

0,26 

0,26 

1,99 

0,66 

0,65 

-0,77 

-18,89 

0,26 

-2,63 

0,65 

0,78 

-0,38 

1,30 

-0,88 

1,41 

-1,37 

0,38 

-1,86 

0,63 

-0,75 

0,38 

1,78 

-1,35 

-0,50 

0,17 


Rank 

2007* 

42 

59 

56 

39 

47 

49 

38 

43 

44 

51 

46 

57 

40 

51 

45 

51 

55 

47 

50 

51 

64 

177 

62 

73 

59 

59 

65 

58 

71 

63 

74 

68 

79 

69 

75 

72 

67 

83 

79 

PDI 

2007* 

740 

773 

766 

737 

752 

757 

736 

741 

744 

764 

751 

768 

739 

764 

749 

764 

765 

752 

762 

764 

782 

958 

775 

798 

773 

773 

783 

771 

794 

778 

801 

789 

807 

790 

803 

796 

788 

814 

807 

1147 

Rank 

2009* 

pred. 

37 

20 

32 

59 

44 

47 

48 

49 

61 

50 

52 

55 

46 

52 

74 

55 

55 

63 

55 

60 

54 

3 

64 

75 

64 

69 

61 

76 

51 

72 

45 

70 

71 

77 

67 

66 

80 

73 

78 

PDI 

2009* 

pred. 

701 

660 

686 

769 

719 

740 

748 

749 

772 

760 

765 

768 

738 

765 

793 

768 

768 

776 

768 

770 

767 

537 

777 

795 

777 

785 

772 

798 

762 

791 

722 

787 

790 

799 

784 

783 

804 

792 

802 

1148 

Change 


pred. [%] 

-3,31 

-9,09 

-6,03 

4,06 

-2,84 

0,00 

0,94 

0,13 

2,25 

0,53 

0,79 

1,19 

-3,02 

0,13 

3,66 

0,26 

0,13 

1,17 

0,13 

0,13 

-1,16 

-30,89 

0,00 

2,32 

-0,13 

0,77 

-1,03 

2,18 

-3,18 

0,25 

-8,61 

-0,63 

-0,25 

0,50 

-1,63 

-2,00 

0,25 

-1,37 

-0,12 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

-0,09 

67



68 

Rank 


First half** 

79 

79 

81 

82 

83 

84 

85 

86 

87 

88 

88 

88 

88 

88 

93 

93 

95 

96 

96 

98 

99 

100 

100 

102 

103 

104 

105 

106 

106 

108 

108 

110 

110 

110 

113 

114 

115 

116 

117 

Name 

Landshut, county 

Potsdam-Mittelmark, county 

Calw, county 

Straubing-Bogen, county 

Forchheim, county 

Mainz-Bingen, county 

Coesfeld, county 

Oberallgäu, county 

Rhön-Grabfeld, county 

Darmstadt-Dieburg, county 

Freiberg, county 

Freiburg im Breisgau, county 

Saale-Holzland county 

Südwestpfalz, county 

Kaiserslautern, county 

Schwabach, municipality 

Sächsische Schweiz, county 

Nürnberger Land, county 

Tuttlingen, county 

Rheinisch-Bergischer county 

Zollernalbkreis 

Bayreuth, county 

Mittweida, county 

Cochem-Zell, county 

Sömmerda, county 

Löbau-Zittau, county 

Günzburg, county 

Garmisch-Partenkirchen, county 

Kassel, county 

Schwarzwald-Baar county 

St. Wendel, county 

Fulda, county 

Gütersloh, county 

Ingolstadt, municipality 

Schwäbisch Hall, county 

Schwandorf, county 

Leipziger Land, county 

Gießen, county 

Pinneberg, county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

804 

804 

806 

807 

812 

813 

814 

815 

819 

824 

824 

824 

824 

824 

825 

825 

826 

827 

827 

832 

836 

839 

839 

840 

843 

848 

852 

856 

856 

858 

858 

859 

859 

859 

860 

861 

862 

864 

865 

1149 

Change 


[%] 

-0,25 

2,29 

1,77 

-2,06 

-0,37 

0,74 

1,24 

0,49 

-0,73 

1,23 

-0,60 

0,12 

0,86 

-2,14 

-0,60 

0,12 

1,10 

0,49 

0,85 

2,09 

-1,07 

-1,53 

-0,71 

0,96 

-0,94 

1,44 

-0,47 

0,12 

0,82 

-1,15 

1,90 

-1,72 

0,82 

1,18 

-1,83 

-0,92 

0,58 

-1,26 

0,35 

0,17 

Rank 

2007* 

78 

66 

70 

92 

85 

79 

76 

82 

94 

83 

95 

90 

87 

99 

96 

92 

87 

90 

89 

85 

101 

106 

101 

97 

105 

98 

110 

108 

103 

118 

99 

122 

106 

103 

124 

120 

111 

123 

114 

PDI 

2007* 

806 

786 

792 

824 

815 

807 

804 

811 

825 

814 

829 

823 

817 

842 

830 

824 

817 

823 

820 

815 

845 

852 

845 

832 

851 

836 

856 

855 

849 

868 

842 

874 

852 

849 

876 

869 

857 

875 

862 

1147 

Rank 

2009* 

pred. 

84 

84 

95 

67 

83 

89 

90 

93 

90 

97 

82 

90 

96 

80 

104 

100 

103 

97 

78 

117 

88 

87 

102 

112 

101 

113 

107 

109 

117 

107 

127 

105 

115 

138 

106 

111 

123 

110 

120 

PDI 

2009* 

pred. 

818 

818 

828 

784 

813 

821 

822 

823 

822 

830 

810 

822 

829 

804 

843 

831 

837 

830 

802 

866 

820 

819 

834 

855 

832 

859 

849 

851 

866 

849 

876 

846 

865 

889 

847 

854 

871 

852 

867 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

1,74 

1,74 

2,73 

-2,85 

0,12 

0,98 

0,98 

0,98 

0,37 

0,73 

-1,70 

-0,24 

0,61 

-2,43 

2,18 

0,73 

1,33 

0,36 

-3,02 

4,09 

-1,91 

-2,38 

-0,60 

1,79 

-1,30 

1,30 

-0,35 

-0,58 

1,17 

-1,05 

2,10 

-1,51 

0,70 

3,49 

-1,51 

-0,81 

1,04 

-1,39 

0,23 

-0,09


Rank 


First half** 

118 

119 

120 

121 

122 

122 

124 

125 

126 

127 

128 

128 

130 

131 

132 

132 

134 

134 

136 

136 

138 

138 

140 

141 

142 

142 

144 

145 

146 

147 

148 

148 

150 

151 

152 

153 

153 

153 

153 

Name 

Siegen-Wittgenstein, county 

Darmstadt, municipality 

Würzburg, municipality 

Göppingen, county 

Passau, county 

Riesa-Großenhain, county 

Ahrweiler, county 

Ulm, Stadt county 

Offenbach, county 

Vogtland county 

Annaberg, county 

Konstanz, county 

Karlsruhe, Stadt county 

Ostallgäu, county 

Stuttgart, Stadt county 

Waldshut, county 

Freyung-Grafenau, county 

Heidenheim, county 

Meißen, county 

Spree-Neiße, county 

Emmendingen, county 

Warendorf, county 

Lörrach, county 

Bad Dürkheim, county 

Dillingen a.d.Donau, county 

Rhein-Sieg county 

Sigmaringen, county 

Bergstraße, county 

Südliche Weinstraße, county 

Ostalb county 

Limburg-Weilburg, county 

Oberspreewald-Lausitz, county 

Bautzen, county 

Deggendorf, county 

Aachen, municipality 

Chemnitzer Land, county 

Groß-Gerau, county 

Mühldorf a. Inn, county 

Wolfsburg, municipality 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

866 

867 

870 

873 

874 

874 

876 

877 

878 

879 

881 

881 

883 

885 

888 

888 

889 

889 

893 

893 

899 

899 

902 

904 

905 

905 

906 

908 

909 

917 

920 

920 

923 

924 

926 

927 

927 

927 

927 

1149 

Change 


[%] 

1,29 

1,05 

-0,34 

0,92 

-0,68 

1,16 

1,86 

-3,31 

1,50 

1,27 

0,46 

0,46 

-0,23 

-0,45 

-0,67 

-6,53 

-2,31 

-0,89 

0,11 

0,22 

0,56 

1,47 

0,33 

-0,22 

-4,03 

2,38 

-2,05 

-1,41 

-0,55 

-0,86 

1,43 

0,66 

-2,64 

-2,33 

1,87 

0,43 

0,00 

1,87 

-3,03 

0,17 


Rank 

2007* 

108 

112 

121 

116 

127 

115 

113 

139 

116 

118 

125 

125 

129 

131 

134 

169 

142 

136 

133 

132 

134 

130 

137 

138 

161 

128 

151 

147 

144 

151 

139 

144 

167 

165 

141 

148 

155 

142 

176 

PDI 

2007* 

855 

858 

873 

865 

880 

864 

860 

907 

865 

868 

877 

877 

885 

889 

894 

950 

910 

897 

892 

891 

894 

886 

899 

906 

943 

884 

925 

921 

914 

925 

907 

914 

948 

946 

909 

923 

927 

910 

956 

1147 

Rank 

2009* 

pred. 

126 

127 

115 

114 

121 

130 

139 

97 

142 

137 

132 

136 

129 

125 

131 

94 

117 

122 

132 

139 

148 

152 

145 

148 

123 

156 

142 

135 

144 

151 

172 

154 

139 

146 

189 

159 

153 

167 

146 

PDI 

2009* 

pred. 

875 

876 

865 

863 

868 

879 

891 

830 

895 

887 

882 

884 

877 

873 

880 

827 

866 

869 

882 

891 

908 

912 

898 

908 

871 

921 

895 

883 

897 

910 

949 

920 

891 

904 

978 

931 

917 

943 

904 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

1,04 

1,04 

-0,57 

-1,15 

-0,69 

0,57 

1,71 

-5,36 

1,94 

0,91 

0,11 

0,34 

-0,68 

-1,36 

-0,90 

-6,87 

-2,59 

-2,25 

-1,23 

-0,22 

1,00 

1,45 

-0,44 

0,44 

-3,76 

1,77 

-1,21 

-2,75 

-1,32 

-0,76 

3,15 

0,00 

-3,47 

-2,16 

5,62 

0,43 

-1,08 

1,73 

-2,48 

-0,09 

69



70 

Rank 


First half** 

157 

158 

159 

159 

161 

162 

163 

164 

165 

166 

167 

168 

168 

168 

171 

172 

172 

174 

174 

174 

177 

178 

179 

180 

180 

180 

183 

184 

185 

185 

187 

187 

189 

189 

189 

192 

192 

194 

194 

Name 

Neustadt a.d. Aisch-Bad Windsheim, r.d. 

Main-Kinzig county 

Aue-Schwarzenberg, county 

Wittenberg, county 

Rhein county Neuss 

Wetterau county 

Ortenau county 

Tirschenreuth, county 

Paderborn, county 

Bonn, municipality 

Potsdam, municipality 

Hildburghausen, county 

Muldental county 

Saalfeld-Rudolstadt, county 

Ilm county 

Regensburg, municipality 

Saale-Orla county 

Dresden, municipality 

Germersheim, county 

Haßberge, county 

Segeberg, county 

Göttingen, county 

Baden-Baden, Stadt county 

Kelheim, county 

Neckar-Odenwald county 

Zwickauer Land, county 

Rendsburg-Eckernförde, county 

Elbe-Elster, county 

Greifswald, municipality 

Greiz, county 

Birkenfeld, county 

Cham, county 

Bernkastel-Wittlich, county 

Kitzingen, county 

Merzig-Wadern, county 

Osnabrück, county 

Stade, county 

Bitburg-Prüm, county 

Mettmann, county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

929 

930 

931 

931 

933 

934 

936 

937 

942 

943 

944 

945 

945 

945 

950 

951 

951 

953 

953 

953 

955 

957 

961 

964 

964 

964 

965 

973 

975 

975 

976 

976 

978 

978 

978 

979 

979 

981 

981 

1149 

Change 


[%] 

-0,64 

0,65 

0,87 

-0,32 

1,74 

0,21 

0,54 

-3,00 

1,73 

1,84 

1,29 

-0,84 

-0,11 

-1,05 

-0,21 

0,00 

-0,83 

0,85 

-1,24 

-3,25 

0,42 

1,48 

1,37 

-0,92 

0,31 

-0,72 

1,05 

0,41 

-1,91 

1,67 

3,28 

-0,41 

-0,91 

-0,41 

1,77 

0,31 

0,93 

-2,10 

1,76 

0,17 

Rank 

2007* 

160 

150 

148 

159 

146 

157 

156 

184 

153 

153 

157 

173 

165 

174 

172 

170 

178 

163 

183 

195 

170 

161 

167 

189 

180 

187 

174 

185 

201 

178 

163 

193 

196 

194 

180 

190 

186 

208 

182 

PDI 

2007* 

935 

924 

923 

934 

917 

932 

931 

966 

926 

926 

932 

953 

946 

955 

952 

951 

959 

945 

965 

985 

951 

943 

948 

973 

961 

971 

955 

969 

994 

959 

945 

980 

987 

982 

961 

976 

970 

1002 

964 

1147 

Rank 

2009* 

pred. 

158 

162 

162 

157 

162 

175 

166 

148 

181 

172 

171 

160 

161 

169 

176 

174 

170 

179 

132 

154 

179 

185 

182 

165 

167 

177 

187 

193 

178 

195 

215 

185 

183 

183 

190 

195 

195 

192 

198 

PDI 

2009* 

pred. 

929 

938 

938 

927 

938 

952 

942 

908 

959 

949 

946 

935 

937 

944 

954 

951 

945 

958 

882 

920 

958 

968 

961 

941 

943 

955 

975 

981 

957 

984 

1018 

968 

967 

967 

979 

984 

984 

980 

990 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

0,00 

0,86 

0,75 

-0,43 

0,54 

1,93 

0,64 

-3,09 

1,80 

0,64 

0,21 

-1,06 

-0,85 

-0,11 

0,42 

0,00 

-0,63 

0,52 

-7,45 

-3,46 

0,31 

1,15 

0,00 

-2,39 

-2,18 

-0,93 

1,04 

0,82 

-1,85 

0,92 

4,30 

-0,82 

-1,12 

-1,12 

0,10 

0,51 

0,51 

-0,10 

0,92 

-0,09


Rank 


First half** 

196 

197 

197 

199 

200 

201 

202 

202 

204 

204 

206 

207 

208 

208 

210 

211 

211 

213 

214 

215 

216 

217 

218 

218 

220 

220 

222 

223 

223 

223 

226 

227 

228 

229 

229 

231 

232 

232 

234 

Name 

Hoyerswerda, municipality 

Gotha, county 

Vogelsberg county 

Bad Kissingen, county 

Dingolfing-Landau, county 

Neuwied, county 

Osnabrück, municipality 

Weimarer-Land, county 

Schmalkalden-Meiningen, county 

Wolfenbüttel, county 

Steinfurt, county 

Rosenheim, municipality 

Alzey-Worms, county 

Oberbergischer county 

Saarpfalz county 

Bamberg, municipality 

Döbeln, county 

Olpe, county 

Minden-Lübbecke, county 

Miltenberg, county 

Coburg, county 

Viersen, county 

Saarlouis, county 

Schwalm-Eder county 

Parchim, county 

Rhein-Lahn county 

Weißenburg-Gunzenhausen, r. district 

Hamburg, state 

Plön, county 

Regen, county 

Marburg-Biedenkopf, county 

Ennepe-Ruhr county 

Westerwald county 

Wartburg county 

Wesel, county 

Mayen-Koblenz, county 

Gifhorn, county 

Schweinfurt, municipality 

Lahn-Dill county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

983 

985 

985 

989 

991 

995 

996 

996 

1001 

1001 

1002 

1004 

1007 

1007 

1009 

1011 

1011 

1013 

1018 

1019 

1020 

1021 

1023 

1023 

1026 

1026 

1028 

1029 

1029 

1029 

1031 

1032 

1033 

1034 

1034 

1039 

1041 

1041 

1042 

1149 

Change 


[%] 

1,24 

0,72 

-1,99 

-0,50 

0,41 

0,81 

0,00 

0,40 

-0,20 

-0,20 

0,50 

0,40 

1,00 

2,03 

3,17 

-12,39 

-1,27 

0,50 

1,50 

-1,36 

-1,35 

1,19 

2,30 

-1,06 

-2,29 

0,39 

0,19 

0,00 

-0,58 

0,59 

-1,62 

1,18 

0,39 

-0,86 

1,97 

0,48 

1,46 

0,68 

-0,38 

0,17 


Rank 

2007* 

187 

191 

212 

201 

196 

196 

203 

200 

209 

209 

204 

206 

204 

196 

191 

302 

220 

213 

209 

227 

228 

214 

206 

228 

245 

218 

221 

223 

232 

219 

243 

217 

223 

236 

216 

228 

221 

228 

240 

PDI 

2007* 

971 

978 

1005 

994 

987 

987 

996 

992 

1003 

1003 

997 

1000 

997 

987 

978 

1154 

1024 

1008 

1003 

1033 

1034 

1009 

1000 

1034 

1050 

1022 

1026 

1029 

1035 

1023 

1048 

1020 

1029 

1043 

1014 

1034 

1026 

1034 

1046 

1147 

Rank 

2009* 

pred. 

199 

194 

187 

190 

212 

201 

201 

204 

204 

200 

208 

210 

215 

221 

220 

84 

215 

215 

231 

201 

207 

228 

231 

214 

206 

233 

222 

212 

219 

226 

211 

235 

229 

222 

242 

235 

248 

239 

225 

PDI 

2009* 

pred. 

992 

982 

975 

979 

1014 

995 

995 

997 

997 

994 

1003 

1010 

1018 

1024 

1023 

818 

1018 

1018 

1038 

995 

1001 

1035 

1038 

1015 

998 

1040 

1027 

1014 

1021 

1033 

1013 

1046 

1036 

1027 

1051 

1046 

1065 

1047 

1030 

1148 

Change 


pred. [%] 

0,92 

-0.30 

-1,02 

-1,01 

2,32 

0,00 

-0,10 

0,10 

-0,40 

-0,70 

0,10 

0,60 

1,09 

1,69 

1,39 

-19,09 

0,69 

0,49 

1,96 

-2,36 

-1,86 

1,37 

1,47 

-0,78 

-2,73 

1,36 

-0,10 

-1,46 

-0,78 

0,39 

-1,75 

1,36 

0,29 

-0,68 

1,64 

0,67 

2,31 

0,58 

-1,15 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

-0,09 

71



72 

Rank 


First half** 

234 

236 

236 

236 

236 

240 

240 

242 

243 

244 

245 

246 

247 

248 

248 

248 

251 

252 

252 

254 

254 

256 

257 

258 

258 

258 

258 

258 

263 

263 

263 

266 

267 

267 

267 

270 

271 

271 

273 

Name 

Oldenburg, county 

Altenburger Land, county 

Grafschaft Bentheim, county 

Kronach, county 

Lichtenfels, county 

Dahme-Spreewald, county 

Höxter, county 

Hof, county 

Leverkusen, municipality 

Frankfurt am Main, municipality 

Neustadt a. d. Weinstraße, municipality 

Havelland, county 

Erftkreis 

Bad Kreuznach, county 

Börde, county 

Osterholz, county 

Emsland, county 

Cuxhaven, county 

Lüchow-Dannenberg, county 

Köln, municipality 

Passau, municipality 

Suhl, municipality 

Schleswig-Flensburg, county 

Donnersberg county 

Hannover, region 

Lippe, county 

Ostvorpommern, county 

Speyer, municipality 

Ammerland, county 

Diepholz, county 

Kulmbach, county 

Heilbronn, county 

Koblenz, municipality 

Nordvorpommern, county 

Oberhavel, county 

Mülheim an der Ruhr, municipality 

Burgenland county 

Prignitz, county 

Mecklenburg-Strelitz, county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

1042 

1044 

1044 

1044 

1044 

1045 

1045 

1048 

1049 

1050 

1051 

1053 

1055 

1064 

1064 

1064 

1074 

1080 

1080 

1081 

1081 

1082 

1086 

1087 

1087 

1087 

1087 

1087 

1088 

1088 

1088 

1092 

1093 

1093 

1093 

1099 

1100 

1100 

1101 

1149 

Change 


[%] 

0,48 

1,46 

-1,69 

-2,70 

0,10 

0,19 

-0,67 

0,29 

1,75 

-0,10 

0,29 

1,25 

1,74 

1,72 

-0,19 

1,62 

-0,46 

7,04 

-1,73 

-0,28 

-0,92 

-0,46 

0,46 

-1,54 

0,46 

2,94 

-2,51 

-0,09 

-1,81 

-1,45 

0,18 

0,28 

0,28 

0,46 

2,34 

1,20 

0,09 

2,04 

1,38 

0,17 

Rank 

2007* 

233 

223 

249 

252 

236 

236 

247 

239 

226 

246 

243 

235 

233 

240 

250 

242 

254 

214 

272 

257 

268 

261 

255 

275 

256 

248 

283 

262 

277 

275 

258 

264 

266 

262 

251 

258 

272 

253 

258 

PDI 

2007* 

1037 

1029 

1062 

1073 

1043 

1043 

1052 

1045 

1031 

1051 

1048 

1040 

1037 

1046 

1066 

1047 

1079 

1009 

1099 

1084 

1091 

1087 

1081 

1104 

1082 

1056 

1115 

1088 

1108 

1104 

1086 

1089 

1090 

1088 

1068 

1086 

1099 

1078 

1086 

1147 

Rank 

2009* 

pred. 

239 

243 

227 

208 

229 

222 

235 

241 

258 

234 

235 

247 

253 

258 

246 

263 

251 

305 

245 

248 

253 

256 

260 

255 

262 

285 

243 

269 

252 

257 

266 

267 

268 

275 

275 

270 

270 

278 

280 

PDI 

2009* 

pred. 

1047 

1054 

1034 

1003 

1036 

1027 

1046 

1048 

1079 

1042 

1046 

1062 

1071 

1079 

1061 

1089 

1068 

1151 

1059 

1065 

1071 

1074 

1085 

1072 

1088 

1121 

1054 

1100 

1069 

1078 

1095 

1096 

1097 

1113 

1113 

1101 

1101 

1114 

1117 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

0,48 

0,96 

-0,96 

-3,93 

-0,77 

-1,72 

0,10 

0,00 

2,86 

-0,76 

-0,48 

0,85 

1,52 

1,41 

-0,28 

2,35 

-0,56 

6,57 

-1,94 

-1,48 

-0,93 

-0,74 

-0,09 

-1,38 

0,09 

3,13 

-3,04 

1,20 

-1,75 

-0,92 

0,64 

0,37 

0,37 

1,83 

1,83 

0,18 

0,09 

1,27 

1,45 

-0,09


Rank 


First half** 

274 

274 

276 

277 

278 

279 

279 

281 

282 

283 

283 

285 

286 

287 

288 

288 

288 

291 

292 

293 

294 

295 

296 

296 

298 

298 

298 

301 

302 

303 

304 

305 

306 

307 

307 

309 

309 

311 

312 

Name 

Bad Doberan, county 

Chemnitz, municipality 

Peine, county 

Daun, county 

Nordfriesland, county 

Augsburg, municipality 

Kleve, county 

Mansfeld-Südharz, county 

Hochsauerland county 

Cottbus, municipality 

Trier, municipality 

Verden, county 

Unna, county 

Ludwigslust, county 

Herzogtum Lauenburg, county 

Landshut, municipality 

Wiesbaden, Landeshauptstadt, county 

Delitzsch, county 

Sonneberg, county 

Weimar, municipality 

Heinsberg, county 

Ostholstein, county 

Düsseldorf, municipality 

Torgau-Oschatz, county 

Coburg, municipality 

Recklinghausen, county 

Vechta, county 

Kusel, county 

Nordwestmecklenburg, county 

Bottrop, municipality 

Barnim, county 

Erfurt, municipality 

Waldeck-Frankenberg, county 

Aurich, county 

Landau in der Pfalz, municipality 

Anhalt-Bitterfeld, county 

Görlitz, municipality 

Nordhausen, county 

Braunschweig, municipality 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

1102 

1102 

1104 

1105 

1107 

1112 

1112 

1114 

1115 

1116 

1116 

1117 

1122 

1123 

1124 

1124 

1124 

1126 

1127 

1132 

1133 

1134 

1135 

1135 

1136 

1136 

1136 

1138 

1142 

1146 

1149 

1152 

1153 

1161 

1161 

1162 

1162 

1164 

1168 

1149 

Change 


[%] 

-1,25 

1,19 

0,73 

-1,34 

-0,09 

2,02 

1,37 

1,64 

0,54 

0,36 

-0,53 

-0,71 

1,91 

0,63 

0,09 

0,99 

0,54 

0,36 

1,26 

0,53 

1,43 

0,53 

0,35 

-1,22 

-0,18 

1,07 

-1,73 

-2,90 

-0,87 

2,05 

-0,61 

0,09 

-6,41 

-0,17 

-1,61 

-0,51 

0,35 

-2,18 

1,21 


Rank 

2007* 


0,17 

284 

264 

269 

288 

277 

266 

271 

269 

279 

280 

289 

294 

274 

284 

291 

281 

287 

289 

281 

295 

286 

296 

297 

299 

298 

293 

304 

316 

301 

291 

304 

300 

347 

309 

321 

313 

307 

328 

302 

PDI 

2007* 

1116 

1089 

1096 

1120 

1108 

1090 

1097 

1096 

1109 

1112 

1122 

1125 

1101 

1116 

1123 

1113 

1118 

1122 

1113 

1126 

1117 

1128 

1131 

1149 

1138 

1124 

1156 

1172 

1152 

1123 

1156 

1151 

1232 

1163 

1180 

1168 

1158 

1190 

1154 

1147 

Rank 

2009* 

pred. 

260 

280 

275 

263 

273 

287 

293 

298 

284 

292 

274 

272 

302 

282 

290 

296 

295 

300 

299 

285 

304 

300 

287 

283 

293 

302 

279 

265 

289 

311 

296 

307 

250 

308 

290 

309 

339 

305 

316 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 

2009* 

pred. 

1085 

1117 

1113 

1089 

1106 

1123 

1129 

1137 

1120 

1126 

1109 

1105 

1147 

1118 

1125 

1133 

1130 

1143 

1139 

1121 

1150 

1143 

1123 

1119 

1129 

1147 

1115 

1093 

1124 

1168 

1133 

1152 

1067 

1153 

1125 

1154 

1220 

1151 

1182 

1148 

Change 


pred. [%] 

-1,54 

1,36 

0,82 

-1,45 

-0,09 

0,99 

1,53 

2,06 

0,45 

0,90 

-0,63 

-1,07 

2,23 

-0,45 

0,09 

0,80 

0,53 

1,51 

1,06 

-0,97 

1,50 

0,79 

-1,06 

-1,41 

-0,62 

0,97 

-1,85 

-3,95 

-1,58 

1,92 

-1,39 

0,00 

-7,46 

-0,69 

-3,10 

-0,69 

4,99 

-1,12 

1,20 

-0,09 

73



74 

Rank 


First half** 

313 

313 

315 

316 

316 

318 

319 

320 

320 

320 

323 

324 

324 

326 

327 

327 

329 

329 

331 

331 

333 

334 

334 

336 

337 

338 

338 

340 

341 

342 

343 

343 

345 

346 

347 

348 

348 

350 

351 

Name 

Saale county 

Schaumburg, county 

Uckermark, county 

Borken, county 

Bremen, municipality 

Hersfeld-Rotenburg, county 

Northeim, county 

Ansbach, municipality 

Müritz, county 

Nürnberg, municipality 

Lüneburg, county 

Euskirchen, county 

Kempten (Allgäu), municipality 

Weiden i.d.OPf., municipality 

Hildesheim, county 

Oldenburg (Oldenburg), municipality 

Amberg, municipality 

Stendal, county 

Aachen, county 

Rügen, county 

Helmstedt, county 

Harz, county 

Kyffhäuser county 

Osterode am Harz, county 

Oder-Spree, county 

Memmingen, municipality 

Teltow-Fläming, county 

Frankenthal (Pfalz), municipality 

Nienburg (Weser), Landkreis 

Ostprignitz-Ruppin, county 

Bayreuth, municipality 

Soest, county 

Cloppenburg, county 

Uecker-Randow, county 

Goslar, county 

Aschaffenburg, municipality 

Wismar, municipality 

Dessau-Roßlau, municipality 

Altenkirchen (Westerwald), county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

1171 

1171 

1174 

1176 

1176 

1179 

1181 

1184 

1184 

1184 

1187 

1189 

1189 

1191 

1192 

1192 

1199 

1199 

1200 

1200 

1201 

1203 

1203 

1205 

1207 

1208 

1208 

1209 

1213 

1216 

1218 

1218 

1219 

1224 

1225 

1230 

1230 

1231 

1235 

1149 

Change 


[%] 

0,26 

0,95 

1,56 

-1,01 

0,51 

0,08 

1,37 

-0,92 

1,54 

-0,84 

0,34 

1,89 

-0,92 

-0,17 

0,76 

0,34 

-0,75 

2,04 

2,21 

-2,44 

1,09 

-0,58 

-0,91 

1,35 

1,43 

2,46 

0,25 

0,42 

-0,33 

1,33 

0,91 

0,66 

-1,22 

0,99 

1,32 

-0,32 

-1,13 

1,07 

-1,59 

0,17 

Rank 

2007* 

313 

308 

304 

324 

315 

319 

310 

332 

311 

331 

322 

312 

333 

330 

322 

324 

338 

318 

317 

346 

324 

340 

343 

327 

328 

320 

336 

335 

344 

333 

337 

340 

348 

342 

339 

348 

350 

345 

353 

PDI 

2007* 

1168 

1160 

1156 

1188 

1170 

1178 

1165 

1195 

1166 

1194 

1183 

1167 

1200 

1193 

1183 

1188 

1208 

1175 

1174 

1230 

1188 

1210 

1214 

1189 

1190 

1179 

1205 

1204 

1217 

1200 

1207 

1210 

1234 

1212 

1209 

1234 

1244 

1218 

1255 

1147 

Rank 

2009* 

pred. 

314 

316 

326 

310 

319 

314 

325 

323 

340 

313 

321 

351 

316 

349 

327 

320 

335 

340 

347 

311 

346 

322 

323 

337 

337 

327 

331 

334 

357 

344 

350 

336 

329 

352 

355 

333 

330 

355 

344 

PDI 

2009* 

pred. 

1175 

1182 

1198 

1157 

1189 

1175 

1197 

1195 

1222 

1171 

1192 

1238 

1182 

1229 

1201 

1191 

1217 

1222 

1227 

1168 

1225 

1194 

1195 

1219 

1219 

1201 

1211 

1216 

1250 

1224 

1230 

1218 

1204 

1239 

1247 

1214 

1208 

1247 

1224 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

0,34 

0,94 

2,04 

-1,62 

1,11 

-0,34 

1,35 

0,93 

3,21 

-1,10 

0,42 

4,12 

-0,59 

3,19 

0,76 

-0,08 

1,50 

1,92 

2,25 

-2,67 

2,00 

-0,75 

-0,67 

1,16 

0,99 

-0,58 

0,25 

0,58 

3,05 

0,66 

0,99 

0,00 

-1,23 

1,23 

1,80 

-1,30 

-1,79 

1,30 

-0,89 

-0,09


Rank 


First half** 

352 

353 

354 

355 

356 

357 

358 

359 

360 

361 

361 

363 

364 

364 

366 

367 

368 

368 

370 

371 

371 

373 

374 

375 

376 

376 

378 

379 

379 

381 

382 

383 

383 

385 

386 

387 

388 

389 

390 

Name 

Pforzheim, county 

Hameln-Pyrmont, county 

Mannheim, county 

Bielefeld, municipality 

Remscheid, municipality 

Unstrut-Hainich-Kreis 

Essen, municipality 

Zweibrücken, municipality 

Salzland county 

Emden, municipality 

Herford, county 

Düren, county 

Märkischer county 

Steinburg, county 

Jerichower Land, county 

Leipzig, municipality 

Fürth, municipality 

Rotenburg (Wümme), municipality 

Bochum, municipality 

Saarbrücken, Stadtverband 

Salzgitter, municipality 

Werra-Meißner-Kreis 

Demmin, Kreis 

Märkisch-Oderland, county 

Holzminden, county 

Wunsiedel i.Fichtelgebirge, county 

Stralsund, municipality 

Kassel, municipality 

Wesermarsch, county 

Gera, municipality 

Uelzen, county 

Friesland, county 

Kaufbeuren, municipality 

Brandenburg an der Havel, municipality 

Leer, county 

Wittmund, county 

Hagen, municipality 

Güstrow, county 

Neunkirchen, county 

GERMANY 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

1251 

1252 

1255 

1257 

1258 

1259 

1260 

1266 

1268 

1280 

1280 

1287 

1289 

1289 

1293 

1298 

1299 

1299 

1300 

1303 

1303 

1310 

1313 

1316 

1317 

1317 

1319 

1327 

1327 

1329 

1347 

1348 

1348 

1354 

1362 

1364 

1368 

1370 

1372 

1149 

Change 


[%] 

-0,16 

0,40 

-2,18 

-0,16 

-0,32 

-3,45 

0,16 

-1,78 

-0,08 

-3,69 

0,23 

0,78 

1,98 

-0,15 

-2,93 

2,20 

-0,08 

1,01 

0,54 

1,09 

1,09 

-0,23 

-0,53 

0,69 

1,93 

0,61 

-0,98 

0,61 

-0,08 

-0,37 

-1,32 

-0,66 

2,04 

0,82 

-0,66 

0,37 

1,03 

-0,80 

1,40 

0,17 


Rank 

2007* 

352 

351 

362 

355 

356 

371 

354 

364 

358 

379 

360 

360 

357 

367 

380 

359 

370 

363 

369 

364 

364 

374 

376 

372 

368 

373 

380 

375 

378 

382 

390 

387 

377 

383 

392 

388 

386 

394 

385 

PDI 

2007* 

1253 

1247 

1283 

1259 

1262 

1304 

1258 

1289 

1269 

1329 

1277 

1277 

1264 

1291 

1332 

1270 

1300 

1286 

1293 

1289 

1289 

1313 

1320 

1307 

1292 

1309 

1332 

1319 

1328 

1334 

1365 

1357 

1321 

1343 

1371 

1359 

1354 

1381 

1353 

1147 

Rank 

2009* 

pred. 

363 

359 

332 

360 

358 

343 

348 

353 

361 

340 

362 

364 

372 

368 

354 

380 

367 

375 

366 

369 

365 

371 

369 

372 

382 

380 

377 

379 

377 

374 

376 

382 

388 

386 

382 

385 

389 

387 

396 

PDI 

2009* 

pred. 

1289 

1256 

1213 

1257 

1252 

1223 

1228 

1243 

1267 

1222 

1279 

1297 

1312 

1302 

1244 

1338 

1301 

1327 

1300 

1308 

1299 

1309 

1308 

1312 

1343 

1338 

1334 

1337 

1334 

1313 

1328 

1343 

1379 

1351 

1343 

1347 

1385 

1357 

1394 

1148 

Change 


pred. [%] 


• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

3,04 

0,32 

-3,35 

0,00 

-0,48 

-2,86 

-2,54 

-1,82 

-0,08 

-4,53 

-0,08 

0,78 

1,78 

1,01 

-3,79 

3,08 

0,15 

2,16 

0,00 

0,38 

-0,31 

-0,08 

-0,38 

-0,30 

1,97 

1,59 

1,14 

0,75 

0,53 

-1,20 

-1,41 

-0,37 

2,30 

-0,22 

-1,40 

-1,25 

1,24 

-0,95 

1,60 

-0,09 

75




76 

Rank 


First half** 

390 

392 

393 

393 

395 

396 

397 

398 

399 

400 

401 

402 

403 

404 

405 

406 

407 

408 

409 

410 

411 

412 

413 

414 

415 

416 

417 

418 

419 

420 

421 

422 

423 

424 

425 

426 

427 

428 

429 

Name 

Plauen, municipality 

Dortmund, municipality 

Oberhausen, municipality 

Odenwald municipality 

Celle, county 

Altmark county Salzwedel 

Kaiserslautern, municipality 

Dithmarschen, county 

Krefeld, municipality 

Soltau-Fallingbostel, county 

Zwickau, municipality 

Frankfurt (Oder), municipality 

Neubrandenburg, municipality 

Rostock, municipality 

Lübeck, Hansestadt, municipality 

Solingen, municipality 

Ludwigshafen am Rhein, municipality 

Hamm, municipality 

Kiel, Landeshauptstadt, municipality 

Berlin, Land 

Straubing, municipality 

Herne, municipality 

Magdeburg, municipality 

Halle (Saale), municipality 

Worms, municipality 

Gelsenkirchen, municipality 

Wuppertal, municipality 

Schwerin, municipality 

Eisenach, municipality 

Offenbach am Main, municipality 

Hof, municipality 

Duisburg, municipality 

Neumünster, municipality 

Flensburg, municipality 

Bremerhaven, municipality 

Delmenhorst, municipality 

Mönchengladbach, municipality 

Wilhelmshaven, municipality 

Pirmasens, municipality 

GERMANY 

• 

• 

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• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 


First half** 

1372 

1380 

1383 

1383 

1393 

1395 

1402 

1408 

1410 

1414 

1415 

1428 

1438 

1439 

1441 

1442 

1448 

1455 

1459 

1462 

1463 

1486 

1487 

1503 

1526 

1532 

1536 

1552 

1561 

1562 

1564 

1583 

1613 

1634 

1638 

1650 

1751 

1809 

2092 

1149 

Change 


[%] 

2,01 

0,95 

0,73 

-0,22 

-0,50 

-0,71 

0,43 

0,50 

1,22 

-0,49 

-0,70 

4,92 

1,91 

0,14 

0,14 

0,77 

-1,16 

0,90 

0,27 

-0,41 

-2,98 

1,23 

0,13 

-0,07 

0,20 

2,82 

0,99 

-1,21 

-0,32 

1,49 

0,39 

-0,19 

1,90 

-1,45 

-0,79 

0,18 

1,16 

-0,82 

1,31 

0,17 

Rank 

2007* 

384 

391 

393 

395 

398 

400 

397 

399 

396 

402 

403 

389 

401 

405 

406 

404 

409 

407 

408 

410 

415 

410 

412 

414 

417 

413 

416 

421 

420 

418 

419 

423 

422 

426 

425 

424 

427 

428 

429 

PDI 

2007* 

1345 

1367 

1373 

1386 

1400 

1405 

1396 

1401 

1393 

1421 

1425 

1361 

1411 

1437 

1439 

1431 

1465 

1442 

1455 

1468 

1508 

1468 

1485 

1504 

1523 

1490 

1521 

1571 

1566 

1539 

1558 

1586 

1583 

1658 

1651 

1647 

1731 

1824 

2065 

1147 

Rank 

2009* 

pred. 

398 

393 

399 

391 

389 

391 

401 

402 

403 

399 

397 

412 

410 

404 

407 

404 

393 

409 

408 

406 

395 

413 

411 

414 

416 

418 

417 

415 

423 

420 

421 

419 

425 

422 

424 

426 

427 

428 

429 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

PDI 

2009* 

pred. 

1398 

1391 

1400 

1390 

1385 

1390 

1405 

1408 

1430 

1400 

1396 

1481 

1464 

1440 

1460 

1440 

1391 

1463 

1462 

1454 

1392 

1492 

1475 

1520 

1536 

1573 

1552 

1530 

1607 

1588 

1591 

1579 

1634 

1604 

1626 

1650 

1770 

1804 

2118 

1148 

Change 


pred. [%] 

1,90 

0,80 

1,23 

0,51 

-0,57 

-0,36 

0,21 

0,00 

1,42 

-0,99 

-1,34 

3,71 

1,81 

0,07 

1,32 

-0,14 

-3,94 

0,55 

0,21 

-0,55 

-4,85 

0,40 

-0,81 

1,13 

0,66 

2,68 

1,04 

-1,42 

2,95 

1,66 

1,73 

-0,25 

1,30 

-1,84 

-0,73 

0,00 

1,09 

-0,28 

1,24 

-0,09

Imprint 

Herausgeber: 


Kormoranweg 5 

65201 Wiesbaden 

Projektleitung: Tanja Panhans 

Fachliche Expertise: Sven Albrecht, 

Dr. Dogan Argac, Stefanie Daum 

Redaktion: Intellisource GmbH 

Grafik: smavicon 

Layout: schnellerwerben

Herausgeber: 


Kormoranweg 5 

65201 Wiesbaden 

Tel: +49 (0) 611 - 9278 - 888 

Fax: +49 (0) 611 - 9278 - 887 

anfrage@schulden-kompass.de 

www.schulden-kompass.de 

Wir schaffen Vertrauen

Abridged English version of the SCHUFA Credit Compass 2008

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