Formaat: MP4Omvang: 47,2 Mb27 February 2008Online beschikbaar: [01-12-2014]Standard Youtube LicenseUploaded on Jun 11, 2008Video summary of the ALDE workshop "The International Financial Crisis: Its causes and what to do about it?"Event date: 27/02/08 14:00 to 18:00Location: Room ASP 5G2, European Parliament, BrusselsThis workshop will bring together Members of the European Parliament, economists, academics and journalists as well as representatives of the European Commission to discuss the lessons that have to be drawn from the recent financial crisis caused by the US sub-prime mortgage market.With the view of the informal ECOFIN meeting in April which will look at the financial sector supervision and crisis management mechanisms, this workshop aims at debating a wide range of topics including:- how to improve the existing supervisory framework,- how to combat the opacity of financial markets and improve transparency requirements,- how to address the rating agencies' performance and conflict of interest,- what regulatory lessons are to be learnt in order to avoid a repetition of the sub-prime and the resulting credit crunch.PROGRAMME14:00 - 14:10 Opening remarks: Graham Watson, leader of the of the ALDE Group14:10 - 14:25 Keynote speech by Charlie McCreevy, Commissioner for the Internal Market and Services, European Commission14:25 - 14:40 Presentation by Daniel Daianu, MEP (ALDE) of his background paper14:40 - 15:30 Panel I: Current features of the financial systems and the main causes of the current international crisis.-John Purvis, MEP EPP-Eric De Keuleneer, Solvay Business School, Free University of Brussels-Nigel Phipps, Head of European Regulatory Affairs Moody's-Wolfgang Munchau, journalist Financial Times-Robert Priester, European Banking Federation (EBF), Head of Department Banking Supervision and Financial Markets-Ray Kinsella, Director of the Centre for Insurance Studies University College Dublin-Servaas Deroose, Director ECFIN.C, Macroeconomy of the euro area and the EU, European Commission-Leke Van den Burg, MEP PSE-David Smith, Visiting Professor at Derby Business School

This dataset is about books. It has 1 row and is filtered where the book is Bank liquidity and the global financial crisis : the causes and implications of regulatory reform. It features 5 columns: author, publication date, book publisher, and BNB id.

The last three or four decades have seen a remarkable evolution in the institutions that comprise the modern monetary system. The financial crisis of 2007-2009 is a wakeup call that we need a similar evolution in the analytical apparatus and theories that we use to understand that system. Produced and sponsored by the Institute for New Economic Thinking, this course is an attempt to begin the process of new economic thinking by reviving and updating some forgotten traditions in monetary thought that have become newly relevant. Three features of the new system are central. Most important, the intertwining of previously separate capital markets and money markets has produced a system with new dynamics as well as new vulnerabilities. The financial crisis revealed those vulnerabilities for all to see. The result was two years of desperate innovation by central banking authorities as they tried first this, and then that, in an effort to stem the collapse. Second, the global character of the

Federal Reserve data on emergency lending to banks covering the period August 2007 to April 2010 released in batches in Dec 2010, March 2011 and July 2011 as a result of the Dodd-Frank Act and FOIA requests by Bloomberg news and others.

From the Bloomberg page about the data (Aug 2011):

The data were extracted from 29,000 pages of documents and 18 Fed-prepared Microsoft Excel spreadsheets listing more than 21,000 transactions. The records were made public in batches on Dec. 1, 2010, and March 31 and July 6 of this year. The Fed released some of them under the 2010 Dodd-Frank Act and the rest in responses to Freedom of Information Act requests by media outlets including Bloomberg News and related federal court orders. The data covered money borrowed from the central bank from August 2007 through April 2010.

• Bloomberg News visualization using consolidated data (NB: as far as one can tell Bloomberg have not released their consolidated database. Details of data processing).

Data Source

From Bloomberg Story:

The Federal Reserve released thousands of pages of secret loan documents under court order, almost three years after Bloomberg LP first requested details of the central bank’s unprecedented support to banks during the financial crisis.

The records reveal for the first time the names of financial institutions that borrowed directly from the central bank through the so-called discount window. The Fed provided the documents after the U.S. Supreme Court this month rejected a banking industry group’s attempt to shield them from public view.

...

The central bank has never revealed identities of borrowers since the discount window began lending in 1914. The Dodd-Frank law exempted the facility last year when it required the Fed to release details of emergency programs that extended $3.3 trillion to financial institutions to stem the credit crisis. While Congress mandated disclosure of discount-window loans made after July 21, 2010 with a two-year delay, the records released today represent the only public source of details on discount- window lending during the crisis.

Openness

License: presuming public domain as data released from a federal agency.

This research was conducted in Lithuania in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 224 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Lithuania. Researchers revisited establishments interviewed in Lithuania Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Formaat: MP4-fileOmvang: 255,8 MbGeen informatie over auteursrecht beschikbaar.Online beschikbaar: [06-01-2015]Title: The Financial Crisis: Implications for Washington, Wall Street and Main StreetUploaded on Oct 12, 2010Samenvatting:As the crisis in the U.S. financial markets worsened and the credit markets tightened, all eyes were on the Bush administration`s $700 billion bailout plan passed by the U.S. Senate on Oct. 1. Shortly before the Senate voted, a panel of Cornell experts met in Goldwin Smith Hall to discuss the circumstances that led to the collapse and potential courses of action.(Oct 1, 2008 at Cornell University)NB: Datering op YouTube website klopt niet Panelists:- Robert C. Andolina, visiting Senior Lecturer of Finance and former Managing Director at Lehman Brothers- David Easley, Henry Scarborough Professor of Social Sciences- Elizabeth Sanders, Professor of GovernmentThe event was organized by the Cornell International Affairs Review.Standard YouTube License.

Context & Content

Have you ever noticed how bank credit changes over time? In some periods, banks are more willing to lend while at other times, the faucets are closed. These fluctuations in financial conditions are a normal feature of economies all over the world. But to prevent that excess during the "good times" of ample credit eventually over-expose banks to disproportionate risk when things go sour, banking supervisors have created the Countercyclical Capital Buffer, of "CCyB" for short. The CCyB is one of various tools that banking supervisors have to ensure that banks are resilient to economic conditions, thereby preventing future financial crisis.

Less formally, you can think of the CCyB this way: the more "heated" the economy of a certain country is, authorities might choose to activate this tool and require more capital from banks, in effect preventing them from overexposing themselves to this overheated economy. In contrast, when the economy is not overheated or even when it is depressed, authorities are likely to set it to zero (ie, deactivate this tool) so that banks are not constrained by it and could resume lending to jumpstart the economy.

Acknowledgements

This dataset is owned, compiled and updated by the European Systemic Risk Board. I am just a keen user, but not a contributor to this dataset in any way.

Photo by Adeolu Eletu on www.unsplash.com.

Inspiration

The dataset may be interesting both for people interested in economics and banking, but also for data scientists in general. The former group will have the chance to work on a country-level (countries in Europe) time series of CCyB deicisions that includes interesting information, such as a standardised measure of how intense was the credit markets at the time the decision was made.

For data scientists in general, I would highlight the format of this data: the panel consists of decisions made by countries, but the catch is that they were made at different dates; some countries decide their CCyB rate with a specific frequency while others are more loose on that respect; finally, another very interesting aspect of this data for data wrangling is that there are several dates associated with each CCyB decision by a national authority: the day when the authority decided to set a new level (or confirm the existing one); the date that this decision was disclosed to the general public; and the day by which the new rate will be applied. It took me some time to figure out how exactly to transform all of this in a more common type of data series format - I hope this could both inspire you to work and share similar data, but I'm also looking forward to any contributions in terms of code you might have to make it more efficient or clear. Also, if you feel like porting the code to Python, that would be a big learning opportunity for me and others.

ABSTRACT This study sought to analyze the variables that can influence company bankruptcy. For several years, the main studies on bankruptcy reported on the conventional methodologies with the aim of predicting it. In their analyses, the use of accounting variables was massively predominant. However, when applying them, the accounting variables were considered as homogenous; that is, for the traditional models, it was assumed that in all companies the behavior of the indicators was similar, and the heterogeneity among them was ignored. The relevance of the financial crisis that occurred at the end of 2007 is also observed; it caused a major global financial collapse, which had different effects on a wide variety of sectors and companies. Within this context, research that aims to identify problems such as the heterogeneity among companies and analyze the diversities among them are gaining relevance, given that the sector-related characteristics of capital structure and size, among others, vary depending on the company. Based on this, new approaches applied to bankruptcy prediction modeling should consider the heterogeneity among companies, aiming to improve the models used even more. A causal tree and forest were used together with quarterly accounting and sector-related data on 1,247 companies, 66 of which were bankrupt, 44 going bankrupt after 2008 and 22 before. The results showed that there is unobserved heterogeneity when the company bankruptcy processes are analyzed, raising questions about the traditional models such as discriminant analysis and logit, among others. Consequently, with the large volume in terms of dimensions, it was observed that there may be a functional form capable of explaining company bankruptcy, but this is not linear. It is also highlighted that there are sectors that are more prone to financial crises, aggravating the bankruptcy process.

This research was conducted in Romania in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 304 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Romania.

Researchers revisited establishments interviewed in Romania Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Attached, you can find the do-files and databases produced using STATA from the PNAD and PNS databases for the years 1998 to 2019, freely provided by the Brazilian Federal Government.

The Emergency Electricity Payment Scheme (EEPS) is to provide assistance to households in a financial crisis who are unable to pay their electricity debt. As at Friday 9 June 2016 the Emergency Electricity Payment Scheme (EEPS) approved 1,020 applications for the 2016 - 2017 financial year. Note: a new data system was introduced this financial year, when data were transitioned from the old to the new system, some of the “reasons” and “regions” data were not transferred and resulted in the “Null” response category. Dataset contains: Number and % of approved applications by reason for applying (e.g. illness, financial stress, etc.) Number and % approve applications by Regions where approved applicants live Number and % of ATSI identifier

This is the replication package for Public Goods Under Financial Distress by Pawel Janas (JFE). It includes the replication data and replication code for the figures and tables in the manuscript. The README contains more details.I examine the effects of public debt on municipal services and real outcomes during financial crises using a unique archival dataset of U.S. cities from 1924 to 1943. Unlike today’s countercyclical fiscal policies, the Great Depression provides a rare setting to observe fiscal shocks without substantial intergovernmental or Federal Reserve support. My findings show that financial market frictions – especially the need to refinance debt – led cities to sharply cut expenditures, particularly on capital projects and police services. As urban development halted during the Depression, cities with high pre-crisis debt levels faced significant austerity pressures, a decline in population growth, a rise in crime, and a departure of skilled public servants from municipal governments.

ABSTRACT Despite the extensive privatization achievements over the last decades, government ownership of publicly traded companies remains pervasive around the world. Consistent with past evidence of structural change in the beta coefficient during financial crises, the more recent economic recession of 2014 to 2016 in Brazil presents an opportunity to demonstrate the disadvantages of allocating investment in companies that are publicly traded, but are controlled by the government. Constructing a portfolio of publicly traded State Owned Enterprises, we find that the financial crisis produced a significant increase in risk exposure, results that were much more pronounced when compared with a portfolio of privatized companies. The results also indicate that, in addition to a market factor, the poor performance can be explained by controllership. We believe this study adds to the long-standing debate on whether state-owned firms perform worse than private firms, with higher volatility and lower returns, particularly, during a period of financial crisis.

Armut und Arbeitsplatzverlust in der Wirtschaftskrise. Themen: Einschätzung der Veränderung der Armut in der Wohngegend im eigenen Land und in der EU; geschätzter Anteil der Armen im eigenen Land; Schwierigkeiten mit der Bewältigung der anfallenden Kosten im Haushalt; Veränderung der Möglichkeit, sich medizinische Versorgung, Kinderbetreuung und Langzeit-Pflege leisten zu können; Einschätzung der Entwicklung der Rente; Beunruhigung über eigene Armut im Alter (Skalometer); Zahlungsschwierigkeiten in den letzten 12 Monaten; Einschätzung der Entwicklung der wirtschaftlichen Situation des Haushalts; Einschätzung des Risikos, die Miete, Kreditraten, tägliche Konsumartikel sowie Rechnungen und eine unerwartete Ausgabe von 1000 € nicht bezahlen zu können; Wahrscheinlichkeit des Zwangsauszugs aus der Wohnung aufgrund mangelnder Geldmittel; Arbeitsplatzsicherheit; Wahrscheinlichkeit nach angenommener Kündigung innerhalb von sechs Monaten einen neuen Arbeitsplatz zu bekommen (Skalometer). Demographie: Geschlecht; Alter; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad; Haushaltszusammensetzung und Haushaltsgröße; Selbsteinstufung des Lebensstandards (Skala). Zusätzlich verkodet wurde: Befragten-ID; Interviewer-ID; Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region; Gewichtungsfaktor. Social impact of the crisis. Topics: development of poverty in the last twelve months in: residential area, own country, European Union; estimated share of poor people in the own country (in percent); financial difficulties of the own household; changes in the last six months with regard to the affordability of: personal healthcare, childcare, long-term care; expected impact of economic and financial events on personal future pension; concern regarding the appropriateness of personal income in old age (scale); financial difficulties during the last year; expected development of the own financial situation in the next twelve months; assessment of the risk to not being able to: pay rent or mortgage on time, cope with unexpected expense of 1,000 €, repay consumer loans, pay daily consumer items; likelihood to be obliged to leave current accommodation within the next twelve months due to financial reasons; confidence to keep current job in the next twelve months; likelihood to find a new job within six months (scale). Demography: sex; age; age at end of education; occupation; professional position; type of community; household composition and household size; current living standard (scale). Additionally coded was: respondent ID; interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region; weighting factor.

This research was conducted in Turkey in June-July 2009 as part of the first round of The Financial Crisis Survey. Data from 514 establishments was analyzed to quantify the effect of the 2008 global financial crisis on companies in this country. In Turkey, the target sample was restricted to the manufacturing sector.

Researchers revisited manufacturing establishments interviewed in Turkey Enterprise Survey 2008. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

This research was conducted in Kazakhstan in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 233 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Kazakhstan.

Researchers revisited establishments interviewed in Kazakhstan Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

This dataset provides information on the three macroeconomic sectoral balances, covering 195 countries over 45 years.

Macroeconomic analysis often focuses on the 'twin deficits' - the government deficit and the current account deficit. This is an incomplete view which leaves out the private sector balance.

The three sectoral balances must sum up to zero, by accounting identity (UN System of National Accounts 2008):

(S – I) + (T – G) + (M – X) = 0

Economists using the two-dimensional view have famously missed the global financial crisis, while those using accounting models covering all three sectoral balances were able to predict it (Bezemer 2010, Galbraith 2012). However, data on private sector deficits/surpluses is not readily available. Only the public and current account balances are published regularly by the IMF's World Economic Outlook.

Beyond developed countries, looking at the private sector balance is critical for analyzing and crafting policies in developing countries. The frequently recommended policy of 'fiscal consolidation', i.e. reducing public deficits, is revealed in the sectoral balances to also reduce, ceteris paribus, the private sector surplus (or increase its deficit), slowing down or even reversing development and poverty reduction (Assa and Morgan 2025).

The dataset was calculated based on two publicly available series from the IMF World Economic Outlook (downloaded October 2025): General government net lending/borrowing (coded as GOV) and Current account balance (coded as CAB). From this we calculated the private sector balance as PRV = CAB - GOV. We converted CAB to ROW (ROW = -CAB), the rest of the world balance, and made sure that ROW, GOV and PRV add up to zero as required by the national accounting identity. All years containing IMF forecasts were removed.

References:

Assa, J., & Morgan, M. (2025). The General Relativity of Fiscal Space: Theory and Applications. Review of Political Economy, 1-35.

Bezemer, D. J. (2010). Understanding financial crisis through accounting models. Accounting, organizations and society, 35(7), 676-688.

Galbraith, J. K. (2012). Who are these economists, anyway?. In Contributions in Stock-flow Modeling: Essays in Honor of Wynne Godley (pp. 63-75). London: Palgrave Macmillan UK.

United Nations (2008). System of National Accounts 2008. https://unstats.un.org/unsd/nationalaccount/sna2008.asp

This research was conducted in Turkey in June-July 2010 as part of the third round of The Financial Crisis Survey. Data from 364 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Turkey.

Researchers revisited establishments interviewed in Turkey Enterprise Survey 2008. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

A large literature has established that the International Monetary Fund (IMF) is heavily politicized. We argue that this politicization has important consequences for international reserve accumulation and financial crises. The IMF generates moral hazard asymmetrically, reducing the expected costs of risky lending and policies for states that are politically influential vis-à-vis the institution. Using a panel data set covering 1980 to 2010, we show that proxies for political influence over the IMF are associated with outcomes indicative of moral hazard: lower international reserves and more frequent financial crises. We support our causal claims by applying the synthetic control method to Taiwan, which was expelled from the IMF in 1980. Consistent with our predictions, Taiwan's expulsion led to a sharp increase in precautionary international reserves and exceptionally conservative financial policies.

Krise und Regierungshandeln. Vereinheitlichung der Notrufnummern in der EU. Wettbewerb beim öffentlichen Personenverkehr. Landwirtschaft. Cyber-Sicherheit. Themen: 1. Krise und Regierungshandeln: Sparen oder Investieren als Weg aus der Krise; Bewertung von möglichen Maßnahmen des EU-Parlaments als Weg aus der Krise; Präferenz für nationale oder EU-weite Maßnahmen; Einstellung zur Finanztransaktionssteuer; wichtigste Gründe für bzw. gegen eine Finanztransaktionssteuer; Einstellung zur Übernahme von Staatsschulden durch die anderen EU-Mitgliedsländer (Skala); Einstellung zu einer gemeinsamen EU-Haushaltspolitik; Präferenz für automatische Geldstrafen oder Kürzung der finanziellen Unterstützung zur Durchsetzung der Verschuldungsregelung; Kenntnis von Eurobonds sowie Ratingagenturen sowie Einstellung dazu. 2. Vereinheitlichung der Notrufnummern in der EU: Kenntnis der verschiedenen Notrufnummern; Kenntnis der Notrufnummer für Kinder; Kenntnis der Rufnummer für seelischen Beistand (Telefonseelsorge); Kenntnis der EU-Initiative zur Bereitstellung kostenloser Telefon-Beratungsstellen und Hotlines; Informationsquellen über die Beratungsdienste; Kenntnis der Rufnummer in anderen Mitgliedstaaten; Kenntnis von Organisationen, die 116-Beratungsdienste betreiben; Nützlichkeit ausgewählter Beratungsstellen (Skala); ausreichende Informiertheit der Bürger über Beratungsstellen. 3. Wettbewerb beim öffentlichen Personenverkehr: Nutzungshäufigkeit des Schienenverkehrs; Zweck der Nutzung überregionaler und regionaler Züge; wichtigste Beweggründe für eine häufigere Nutzung des Schienenverkehrs; Zufriedenheit mit dem Schienenverkehrssystem im Lande; Meinung zur Privatisierung des Schienenverkehrs; erwarteter Einfluss der Privatisierung auf den Schienenverkehr (Skala); erwartete Nutznießer oder Verlierer der Privatisierung (Passagiere, Betreiber oder Mitarbeiter); erwartete Veränderung staatlicher Förderung bei vermehrtem Wettbewerb im Schienenverkehr; erwartete Veränderungen im Eisenbahnverkehr durch den Wettbewerb; Wichtigkeit von Dienstleistungen aus einer Hand. 4. Landwirtschaft: Besorgnis über ausreichende Nahrungsmittelproduktion in der Zukunft im Lande, in der EU, weltweit; Befürwortung einer Nahrungsmittelversorgung in der EU durch Importe, Selbstversorgung oder mit Exportüberschüssen; EU-Agrarproduktion (Skala); wichtigste Kriterien beim Kauf persönlicher Nahrungsmittel (Skala: Qualität, Preis, geografische Herkunft, Marke); Achten auf Gütekennzeichen bei Nahrungsmittel; Bekanntheit von Nahrungsmittelkennzeichen; Einstellung zur Landwirtschaft (Skala: Umweltschutz und Landschaftspflege). 5. Cyber-Sicherheit: Häufigkeit der Internetnutzung; Orte der Internetnutzung (Arbeit, zu Hause, Internet-Cafe); Art der Geräte für den Internetzugriff; Art der Aktivitäten im Netz; Einschätzung der allgemeinen Sicherheit bei Aktivitäten wie Online-Banking und Online-Shopping; Art der Befürchtungen bei Aktivitäten wie Online-Banking oder Online-Shopping; Gewohnheitsveränderung aufgrund der eigenen Sicherheitsbedenken bei der Internetnutzung; Art der Informationsquellen über Cyber-Kriminalität; Selbsteinschätzung der Kenntnisse über Cyber-Kriminalität; Häufigkeit selbst erfahrener Cyber-Kriminalität; persönliche Besorgnis Opfer ausgewählter Formen von Internetkriminalität zu werden; präferierte Anlaufstellen im Falle selbst erlittener Cyber-Angriffe; Besorgnis über Internetkriminalität (Skala); Änderung des eigenen Passworts im letzten Jahr bei ausgewählten Online-Diensten. Demographie: Staatsangehörigkeit; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; Familiensituation; Alter bei Beendigung der Schulbildung; Geschlecht; Alter in Jahren; derzeitige bzw. letzte Berufstätigkeit; Urbanisierungsgrad; Anzahl der Haushaltsmitglieder ab 15 Jahren; Anzahl der Haushaltmitglieder unter 10 Jahren sowie zwischen 10 und 14 Jahren; Besitz eines Festnetzanschlusses und eines Mobilfunktelefons; Besitz langlebiger Wirtschaftsgüter; Schwierigkeiten bei der Begleichung von Rechnungen im letzten Jahr; Selbsteinschätzung der gesellschaftlichen Stellung (Skalometer); Häufigkeit der Internetnutzung zu Hause, am Arbeitsplatz bzw. in der Schule, Universität oder Internetcafe. Zusätzlich verkodet wurde: Befragungsdatum; Befragungsbeginn; Befragungsdauer; Anwesenheit Dritter; Kooperationsbereitschaft; Ortsgröße; Region; Interviewsprache; Gewichtungsfaktor. Crisis and governance. Harmonised numbers of services of social values. Competition in the public transport. Agriculture. Cyber security. Topics: 1 crisis and governance: reduction of public spending or public investments as a way out of the crisis; evaluation of possible measures of the EU Parliament as a way out of the crisis; preference for national or EU-wide measures; attitudes towards a tax on financial transactions; most important reasons for or against a tax on financial transactions ; attitude towards assumption of public debt of allEU member states (scale); attitude towards a common EU budgetary policy; preference for automatic fines or reducing funding for the enforcement of debt settlement; knowledge of and attitudes towards Eurobonds and credit rating agencies. 2 Harmonised numbers of services of social values: knowledge of the different emergency numbers; knowledge of the emergency number for children; knowing the phone number for emotional support (telephone counseling); awareness of the EU initiative to provide free telephone counseling services and hotlines; sourcesof information about counseling services; knowledge of the number in other Member States; knowledge of organizations that operate the 116-advisory services; usefulness of selected counseling services (scale); sufficient knowledge of citizens about counseling services. 3 Railway competition: frequency of travel by trains; purpose of using national and regional trains; most important motivation for increasing frequency of traveling by train; satisfaction with the rail system; attitudes towards privatization of the railways; expected impact of privatization on rail transport (scale); expected beneficiaries or losers of privatization (passengers, operator or employee); expected change in public funding due to increased competition in the rail market; expected changes in rail traffic through competition; importance of services from a single service provider. 4 Agriculture: concern about sufficient food production in the future;; advocacy of a food supply in the EU by imports, self-sufficiency or with export surpluses; EU agricultural production (scale); most important criteria when buying food (scale: quality, price, geographical origin, brand); attention to quality labels for food; awareness of food label; attitude to agriculture (scale: environmental, protection, and landscape management). 5 Cyber security: frequency of internet use; locations of Internet access (work, home, internet cafe); type of device to access the Internet; online activities; Rating of the general safety of activities like online banking and online shopping; concerns about using the Internet for online banking or buying things online; habit change because of concerns about security issues using the Internet; information on cybercrime; self-rated of knowledge about cybercrime; frequency of self-experienced cybercrime; personal concern to be victims of selected forms of cybercrime; preferred points of contact in the case of becoming victim of cybercrimes; concern about cybercrime (scale); change of password during past 12 months for selected online services. Demography: nationality; self-rated position on a left-right continuum, family situation; age at end of education; sex; age; occupation; professional position; degree of urbanization; number of persons in the household aged 15 years and older; number of children in household less than 10 years and 10 to 14 years; own a mobile phone and fixed (landline) phone; have durable goods (entertainment electronics, Internet connection, have a car, a flat/a house have finished paying for or still paying for; Financial difficulties last year; self-assessment on social position (scale); Internet use (at home, at work, at school, university or internet café) Also encoded: survey date; survey beginning; interview duration; presence of third parties; willingness to cooperate; city size; region; interview language; weighting factor.