Too Big To Fail & Too Big To Mitigate

“Too Big To Fail” is the term dubbed to a series of American and world financial firms who’s size and interconnectedness are considered as vital to the health and proper functioning of the world economy. Any failure in the operation of these firms could be disastrous to the world economy,and threaten the stability of financial operations. The documentary “Too Big to Fail” captures the few weeks of uneasiness as markets free-falled after discovering the extend of the number of toxic assets in many “Too Big to Fail” firms were investing in and began failing. Realizing the danger posed by a collapsing housing market and the insolvency of a number of these firms, several influential members of the U.S government and leaders of Wall Street giants had just a number of weeks to avoid a total collapse of financial markets that would have most likely created the Great Depression of the 21st century.

Too Big to Fail depicts the panic that the heads of the Federal Reserve and Treasury had to mitigate in the face of troubled markets. Beginning with Bear Stearns, it wasn’t until Lehman Brothers collapse that many people began to comprehend the magnitude of the impending financial crisis . Too Big to Fail is very dramatic. It’s mostly focused on the decisions made by Henry Paulson and Ben Bernanke as they attempted to draw upon funds necessary for a Wall Street bailout and mergers while reinstating the very regulations they disbanded just years before. While the documentary aims to capture the events leading up to Lehman brothers, I personally found that the film excellently explained to the average American the functioning of the financial markets and the role the government inevitably played in it. It capitalized on the roles several key players involved in the crisis and the means they drew upon to save the markets. There is plenty of tension and uneasiness as I would imagine was ever so present during the crisis. It showed the truth of the careless nature of the markets pre-recession, where banks and other financial firms made numerous bad loans which wound up packaged in sub-prime securities. The documentary concluded with the banks accepting the inject of capital to help them remain afloat. The hopes Paulson and other officials had for this capital was to reduce the credit crunch and stimulate the free movement of capital. However banks did not do so, and kept the capital which to this day remains largely in their coffers.

Overall, the documentary excellently portrayed the economic meltdown that occurred in 2008. In a play-by-play, behind closed doors narrative, we were guided through the breaking news, the troubling realities, and ultimate decisions that they greatest players of the era made to save our financial system. What I enjoyed about the documentary was its’ informative nature which many non-economist can grasp. It accurately followed the progression of events and the ultimate solution on behalf of the government to engage in TARP.

Micro-Financing In The Developing World

Chapter Seven of Poor Economics addresses the issue of microfinance in the developing world. Microfinancing is presented as one of the greatest alternatives in recent years that is able to more effectively fight the war on poverty through the extension of lending to borrowers who normally cannot access loans at standard interest rates. The chapter opens with Banerjee and Duflos expose of statistics that show the unreasonable interest rates which many poor people face. The statistics are captivating and show that the poor can only access these loans through non-traditional institutions which westerners traditionally access financing from. However, I understood the reason why the borrowers faced such high interest rates. They reflect the risk premium many lenders demand due to the high risk of default, which is true since the poor lack the ability to repay loans due to their lack of wealth/collateral. However, page 160 show that these rates are commonly between 40% and 200%. The size of the loans are also diminished in comparison to wealthier borrowers. The chapter explains the multiplier effect which typically occurs under these transactions. Borrowers have a high incentive to default on the loan, which leaders attempt to neutralize through a rise in the rate of interest, which constantly pushes the rates higher and higher, until they become unsustainable as seen by the 40%-200% rate of interest.

The chapter argues in favor of a micro finance scheme which collects weekly loans from a group, which lowers the cost of servicing the loans by loan officers. The lower cost translate into lower rates of interest, which reflects the reduce cost of surveying the use of these loans. The MFI program has the ability to create a sort of coalition of members who are able to support one another despite moments of difficulties. Microfinance allows the poorer populations who do not have access to adequate finance to tap into a cheaper credit channel that can provide them with loans for even the most basic necessities needed for running a small company. Its seems like a credible alternative to the current system which has negative effects on the ability of people to acquire, service, and generate growth from loans which westerners enjoy. In theory, MFIs have the ability to more directly address the issue of poverty in these developing nations. However, the chapter expressed the minimal effects of MFIs. They are not a long term solution to the financing issue millions face. The effects of micro-financing in these areas has only contributed to a 5% to 7% increase in business starts. Another issue is the corrupt nature of many of these governments. The greed in these local communities has the ability to impede the potential growth that can be realized through the access of credit. A 4.69% PER DAY interest rate as seen in Chenni, India stunts growth. The authors seek alternatives to these issue through the presentation of statistics and by relating the hardships millions of poor people face throughout the developing world. In my opinion, the authors did an excellent job of compiling relevant data and relating it a story. It is an effective tool. Following this chapter, I ask myself how can MFIs be optimized to provide further support to local businesses? Afterall, it seems like a viable alternative.

Assignment #8

“America’s Most Violent States” by Micheal B. Sauter, Alexader E.M Hess, and Samuel Weigley is an articles the addressed the number of violent crimes in the United States according to the FBI statistics ( a violent crimes are defined by four types of violent crimes : 1) murder, 2) rape, 3) aggravated assault, 4)robbery. ) The number of violent crimes fell in 2011, across most of the United States falling from 403.6 per 100,000 people in 2010, to 386.3 per 100,000 people in 2011 to 1.2 million cases of violent crimes in 2011. For the fifth year in a row, crimes have been falling across the United States, yet despite the positive national trend, it is not true for all states. The 10 states with the highest crime rates in 2010, were the same states found on the 2010 list, except some of their rankings had changed.

The articles cited many possible reasons and variables which are said to be lined to the occurrence of violent crimes. Many of the states listed suffered from high poverty levels and low education attainment. The articles states that “five have among the lowest scored in both measures”. Yet there were outliers, Alaska, which had the second highest crime rate, but also had the third-lowest poverty rate, while Maryland had the ninth highest violent crime rate but held the second highest proportion of adults with a college degree.

This article prompted me to believe that the education variable may be an important link. While my topic seeks to find the correlation of crime rates as a result of the unemployment rate and income for New York, Los Angles, Chicago, and Houston, I had not considered education as part of my regression. However, an outlier such as Maryland in the article, might raise my concerns of possible multicollinearity, and herteroscedasticity issues that may result. These metropolis’s have large variances in the level of income and educational attainment. I am looking at cities and not states, which may mean that I may need to look at certain sectors in these cities to discover the truth behind the rate of violent crimes to these additional variables ( for example: The Bronx Vs Manhattan). 

The article provided a state by state analysis of the conditions present in regards to violent crimes. Some states have violent crime issues only in major cities, while other has sought to combat violent crimes through additional police funding (Florida, 400 new police officers per 100,000 persons). The FBI provided additional statistics on the causes of these crimes per state. Some state dealt with more homicides (Nevada) than robberies ( New Mexico). Overall, the article provided new insights on crimes in the United States, and helped me formulate new ideas and question that might aid me in answering some discrepancies that might arise when comparing four cities that are more than just geographically different. 


Assignment #7

“The Relationship between Crime and Unemployment” by Matthew D. Melick is one of the major sources I will be using towards my research paper. The article looks at the relationship between crime and unemployment, a relationship most people would believe to be an obvious one, however the article looks at the issue from two different perspectives. The traditional view is “ a high unemployment rate suggest that there fewer employment opportunities available, and thus the opportunity cost of choosing crime over legitimate work is low” and the new perspective is that “as the unemployment rate increases there is a proportionate decrease in the supply of suitable victims because people have less to steal.” It is a “supply of offenders” versus a “supply of victims” divide. The article helped me formulate new thoughts on the subject, as I previously only the “supply of offends” viewpoint. It looked at the unemployment rate in regards to motor vehicle thefts, hypothesizing a negative relationship between the two variables. The article presented three different models, each model correcting for a possible error in the other, which make me believe that I can trust the results. The articles concludes that there is definitely a relationship between high unemployment and higher rates of crime, but is suggest that it’s magnitude is not as large as many people believe. There are social safety nets that prevent people from committing crimes for example. Over all, the article influence a number of ideas I can incorporate in future research on the subject.…1c.1.fQyP25GD14w&pbx=1&bav=on.2,or.r_gc.r_pw.r_qf.&fp=1c2aeea5b974b0a1&bpcl=35466521&biw=1270&bih=572

* The article opens as a PDF file so I cannot give you a direct link. However, the link above will lead you to a results page where the are the first link will lead you directly to the article. Sorry for the inconvenience.


1- Introduction:
A: In recent years, the use of Marijuana and the subject of legalization have exploded onto the national stage. This controversial topic, born from the revolutionary counterculture of the 1960s has grown ever so more controversial after several states across the United States have vouched for its use in medical practice, while other states have sought to decriminalize the possession and recreational use of the drug. Interestingly, this change has stemmed from state capitols rather than from an organized political movement, therefore signaling a potential change in political ideologies and party identification on sociopolitical issues. This research paper seeks to focus on: 1) the extent in which political ideology and political party identification affect views regarding the legalization of marijuana; 2) What are the economic implications of current Marijuana laws and the possible economic effects the potential legalization of Marijuana will have on the economy if sociopolitical views on the subject allow for its legalization.

For economist, the legalization of Marijuana possess many interesting challenges. This reported $113 billion dollar industry has the potential of generating $31.1 sales tax revenue annually, while saving billions of tax dollars currently lost to regulation.

In the next section, I will first address the recent sociopolitical movement in favor of Marijuana Legalization. I will do so by specifically focusing the two major political ideologies: Liberalism and Conservatism. As political parties usually base their political dynamics on their political ideologies (Democrats- Liberals Vs. Republicans –Conservatives), I intend to discover likely individuals are to agree or disagree with legalization based on where he places his or herself on the political and ideological spectrum. Following that I will describe the economic implications some studies have found on the legalization of Marijuana. I will describe their approach to deriving the supposed economic benefit of legalization and what they determined. Finally, in the third section I intend to find the correlation that may exist between party identification and income levels (still dependent on finding data that explicitly states/observes both of these variables.) Lastly, I will report my findings and an errors that might possibly be accounted for.

II. Literature Review
1- Article 1: “Ideological Trends in American Public Opinion
Authors: John P. Robinson & John A. Fleishman

This article argues a growth in liberalism on the issue of legalization of Marijuana. Their analysis supports the idea that ideology typically informs an individual on what stance to take concerning certain issues. However, the article also argues that ideology in the United States is “ill-defined” but when a clear distinction arises on a subject, ideologies affects peoples party identification and their voting patterns in presidential elections. These elections obviously dictate our national / local drug policy.

2- Aritcle 2: “ Who Support Marijuana Legalization?”
Author : Joseph Carroll
This article shows the result of a Gallop Poll that asked American whether the use of marijuana should be made legal in the United States. It shows that the trend of support has increase from 12% in 1969 to over 33% in present days. This article uses several explanatory charts which detail how gender, age , geographical location, education, and party affiliation each affect support for legalization. This facts can be used to show where the movements greatest supporters are, and possibly their reasoning behind their motivations.

3- The Budgetary Implication of Marijuana Prohibition
Article 3: Jeffery A. Miron
The Marijuana Policy Project provided funding to this study which sought to address government prohibition, budgetary implications, and estimates towards savings and revenues generated from legalization. This article comprises excellent data which demonstrate the statistical facts on both ends , that range from arrest , expenditures due to arrest, possible Marijuana tax revenue if legalized. I believe many of the sources listed in the bibliography will be of help when determining how true these statistics and projection are.

4- Other Possible Articles not Yet Considered
1- Lost Taxes And Other Costs of Marijuana Laws – The Bulletin of Cannabis Reform
2- The State of Marijuana Markets 2011 – SeeChange LLC

*** The table below did not copy well to WordPress, the link above should guide you directly to the article from where i will possibly derive data from.

Table 1: Percentage of Arrests Due to Marijuana Prohibition
Total Arrests MJ Possession MJ Sale/Man. Poss % S/M % Poss % /2
1 2 3 4 5 6
Alabama 215587 11501 258 0.053 0.001 0.027
Alaska 40181 1239 200 0.031 0.005 0.015
Arizona 304142 16288 1233 0.054 0.004 0.027
Arkansas 218521 6846 928 0.031 0.004 0.016
California 1428248 50149 12338 0.035 0.009 0.018
Colorado 282787 12067 604 0.043 0.002 0.021
Connecticut 146992 6751 773 0.046 0.005 0.023
Delaware 41515 2151 131 0.052 0.003 0.026
D.C.* 4009 32 0 0.008 0.000 0.004
Florida* 0 0 0 0.043 .006 0.022
Georgia 429674 24321 4093 0.057 0.010 0.028
Hawaii 64463 1110 167 0.017 0.003 0.009
Idaho 76032 2949 219 0.039 0.003 0.019
Illinois* 319920 0 0 0.043 0.006 0.000
Indiana 270022 14484 1806 0.054 0.007 0.027
Iowa 113394 6054 551 0.053 0.005 0.027
Kansas 78285 3277 594 0.042 0.008 0.021
Kentucky* 160899 10669 1188 0.066 0.007 0.033
Louisiana 297098 14941 2526 0.050 0.009 0.025
Maine 57203 3294 554 0.058 0.010 0.029
Maryland 318056 17113 2711 0.054 0.009 0.027
Massachusetts 160342 8975 1365 0.056 0.009 0.028
Michigan 413174 14629 2050 0.035 0.005 0.018
Minnesota 269010 9325 6782 0.035 0.025 0.017
Mississippi 202007 9925 1054 0.049 0.005 0.025
Missouri 322775 13202 1338 0.041 0.004 0.020
Montana 30396 384 35 0.013 0.001 0.006
Nebraska 97324 6787 326 0.070 0.003 0.035
Nevada 148656 3828 933 0.026 0.006 0.013
New Hampshire 50830 3706 550 0.073 0.011 0.036
New Jersey 375049 20285 3058 0.054 0.008 0.027
New Mexico 112829 2966 325 0.026 0.003 0.013
New York 1295374 101739 11309 0.079 0.009 0.039
North Carolina 523920 21179 2539 0.040 0.005 0.020
North Dakota 27846 896 137 0.032 0.005 0.016
Ohio 533364 25420 1863 0.048 0.003 0.024
Oklahoma 166004 11198 1302 0.067 0.008 0.034
Oregon 157748 6336 283 0.040 0.002 0.020
Pennsylvania 493339 16471 5057 0.033 0.010 0.017
Rhode Island 35733 2200 293 0.062 0.008 0.031
South Carolina 216451 14348 2370 0.066 0.011 0.033
South Dakota 41615 2449 153 0.059 0.004 0.029
Tennessee 232486 12869 2586 0.055 0.011 0.028
Texas 1074909 55509 1926 0.052 0.002 0.026
Utah 125553 4192 311 0.033 0.002 0.017
Vermont 17565 632 65 0.036 0.004 0.018
Virginia 303203 13140 1443 0.043 0.005 0.022
Washington 298474 13146 1329 0.044 0.004 0.022
West Virginia 51452 2618 248 0.051 0.005 0.025
Wisconsin 322877 45 16 0.000 0.000 0.000
Wyoming 34243 1633 164 0.048 0.005 0.024

Table 2: Expenditures Attributable to Marijuana Prohibition ($ in millions)
Police Budget Judicial Budget Corrections Budget Total
State Total: MJ Prohib: Total MJ Prohib: Total MJ Prohib. Total MJ Prohib.
Alabama 656 18.28 262 28.56 404 4.04 1,322 51
Alaska 177 3.61 130 14.17 175 1.75 482 20
Arizona 1096 33.79 611 66.60 955 9.55 2,662 110
Arkansas 351 6.99 156 17.00 328 3.28 835 27
California 8703 227.97 6255 681.80 7170 71.70 22,128 981
Colorado 830 19.48 329 35.86 820 8.20 1,979 64
Connecticut 682 19.25 430 46.87 554 5.54 1,666 72
Delaware 166 4.82 90 9.81 228 2.28 484 17
Florida 3738 103.19 1396 152.16 3272 32.72 8,406 288
Georgia 1279 48.38 525 57.23 1375 13.75 3,179 119
Hawaii 222 2.49 180 19.62 153 1.53 555 24
Idaho 207 4.61 102 11.12 191 1.91 500 18
Illinois 3053 84.28 961 104.75 1763 17.63 5,777 207
Indiana 843 28.25 325 35.43 727 7.27 1,895 71
Iowa 426 13.44 253 27.58 298 2.98 977 44
Kansas 430 12.26 206 22.45 349 3.49 985 38
Kentucky 488 19.78 290 31.61 610 6.10 1,388 57
Louisiana 829 27.89 359 39.13 780 7.80 1,968 75
Maine 164 6.31 69 7.52 123 1.23 356 15
Maryland 1120 39.68 489 53.30 1104 11.04 2,713 104
Massachusetts 1479 53.98 628 68.45 795 7.95 2,902 130
Michigan 1792 40.62 905 98.65 1853 18.53 4,550 158
Minnesotta 874 37.18 442 48.18 591 5.91 1,907 91
Mississippi 404 12.03 154 16.79 292 2.92 850 32
Missouri 886 21.79 359 39.13 627 6.27 1,872 67
Montana 136 1.02 66 7.19 125 1.25 327 9
Nebraska 235 8.98 96 10.46 231 2.31 562 22
Nevada 539 10.32 248 27.03 471 4.71 1,258 42
New Hampshire 187 8.84 92 10.03 115 1.15 394 20
New Jersey 2231 78.52 948 103.33 1480 14.80 4,659 197
New Mexico 382 6.12 167 18.20 315 3.15 864 27.47
New York 5717 274.42 2262 246.56 4392 43.92 12,371 564.90
North Carolina 1318 33.03 470 51.23 1159 11.59 2,947 95.85
North Dakota 68 1.43 55 6.00 40 0.40 163 7.82
Ohio 2124 58.03 1158 126.22 1937 19.37 5,219 203.63
Oklahoma 518 21.53 193 21.04 511 5.11 1,222 47.68
Oregon 696 15.23 356 38.80 747 7.47 1,799 61.50
Pennsylvania 2220 59.82 1067 116.30 2221 22.21 5,508 198.33
Rhode Island 211 8.23 105 11.45 139 1.39 455 21.06
South Carolina 653 28.79 179 19.51 559 5.59 1,391 53.89
South Dakota 88 2.91 40 4.36 81 0.81 209 8.08
Tennessee 940 36.47 399 43.49 604 6.04 1,943 86.00
Texas 3204 88.47 1355 147.70 3755 37.55 8,314 273.71
Utah 381 7.30 202 22.02 351 3.51 934 32.83
Vermont 78 1.69 39 4.25 66 0.66 183 6.60
Virginia 1176 31.08 513 55.92 1246 12.46 2,935 99.46
Washington 1007 26.66 470 51.23 1053 10.53 2,530 88.42
West Virginia 171 5.17 108 11.77 184 1.84 463 18.79
Wisconsin 1124 0.13 440 47.96 1030 10.30 2,594 58.39
Wyoming 99 2.83 50 5.45 98 0.98 247 9.26
56,398 1,707.41 26,984 2941.26 48447 484.47 131,829 5,133

Table 4b: State Marijuana Tax Revenue – Consumption Method
*** This chart detailing a projected Tax Revenue did not copy well to WordPress, the link above should guide you directly to the article.

III. – Methodology :
I am not sure on how I will be able to derive an econometric formula that relates political affiliation, political ideology, profits and personal income. As I continue to collect data, I expect to be able to pick up some new variables while dropping others. I really would like to have at least two variables from each subjects that represent something like :

Revenue Generated from Marijuana/ Willingness to Legalize = Political Affiliation – Political Ideology + taxation + sales + income

I feel that the above equation shows that willingness to Legalize is equal to Political affiliation, minus political ideologies (ideologies are a strong factor, and to this day ¾ of Americans are still against legalization), . Taxation and Sales can generate revenue, which I believe will be dependent on personal income and willingness to consume.

IV- Evidence / Conclusions
I believe that my results will show that liberals favor legalization over conservatives and that legalization can produce significant revenues for the United States. Those who favor legalization are more likely to see the significant benefits of a regulated but legal Marijuana economy. It may be difficult relating revenue to political affiliation, yet I believe that political affiliation plays a significant role towards the creation of such a market. Finally my conclusion with summarize my research and explain whether or not my findings are significant and related. I will also suggests other alternative toward improving such I study if I find my results to be inadequate.

* For clarification: I do not support the legalization of Marijuana. I merely seek to understand the motivations fueling change in recent state legislation.

The Nicaraguan Example

In Nicaragua, the second most poorest nation in the western hemisphere, the poverty cycle is a normality and a brain drain is in full swing. To begin to comprehend the context under which Nicaraguan students study, one needs to consider the country’s cultural and political history which have been ravaged by civil war, dictatorships, and a series of natural disasters. Once, one of the worlds’ most progressive nation in terms of literacy and scholastic enrollment, in 2003 an dumbfounding 823,000 children out of 1.55 million failed to finish the school year.

For this assignment, I looked at the Foundation for Sustainable Development for information on the educational system of one of my parents’ home nation. Having traveled to Nicaragua on multiple occasions and having spoken to many family members actively enrolled all three levels of education (primary, secondary, post-secondary ); initially I found nothing wrong with the quality of education the Nicaraguans received. However, after reading the statistical figures present in this article, I surely misunderstood to conditions there. In the 1990s, then president Violeta Chamorro reformed the educational curriculum and decentralized the educational system. The decentralization however resulted in a reduction of resources as schools received less funding from the central government nor were provided with adequate structural assistance.

In 2000, with government expenditures capped at 20% of GDP, ( A conditionality behind IMF loan agreements) the budget of the Ministry of Education also remained frozen at a meager 3% of GDP(at its year 2000 level.) Estimates out of the Ministry of Education show that in order for Nicaragua to achieve the Millennium Development Goals (MDG), the adequate budget should have at least amounted to 4.7% of GDP in this period. However, Poor Economics made me realize that this MDG goal is not as well orchestrated as one would believe it to be. It is easy to build schools, enroll students in them, and pray that education will more in demand, but that does not address the economic feasibility of school enrollment, nor the quality of education they will receive. I can only hope that the Nicaraguan Ministry of Education will follow suite with the MDG, but that it will have a more aggressive educational curriculum which will raise the standard of education in Nicaragua for both those learning and teaching.
Overall, this article on the educational system in Nicaragua explained reasons behind the education gap and the recent movement towards closing it. In 2001, the Ministry of Education implemented “The Child-Friendly and Healthy School Initiative” which was an “ambitious cooperation amongst the ministries of Health, the environment, UNICEF, the Pan American Health Organization” to implement new teaching methodologies, promote hygiene and gender equality, boost school enrollment, and improve sanitation facilities to which in 2001 184 school enrolled in. It resembled similar attempts by other world nations.

Comment: Thank you for making this information publicly available. This article was well written and although it only showed the surface of the internal problems within Nicaragua’s educational system, it is a shows where the country can begin to correct it. The outlook in Nicaragua seems rather bleak but I am glad to have read that the country was committed towards expanding the general scope of the school’s curriculum through under the 2001 initiative. However, I am interested in knowing how Nicaragua plans to integrate resulting pool of educated children. In Poor Economics we note that despite mandatory schooling legislation, other variables need to be taken into consideration. Currently, students graduating for Nicaragua’s Universities have trouble finding employment. Frustrated, they take on jobs that make no use of their skills. If we want to make education the norm and valued in this society, it will take more than just school building and funding.

Topic, Thesis, & Data

Topic: The Transnational Transmission of Sovereign Debt Crisis’s in the Euro Area.

Thesis: The financial crisis due to debt burden of several euro-area members is being  transmitted throughout the monetary union, threatening the financial stability of other member nations.

For my final research paper I chose to research the current sovereign debt crisis in Europe. My interest in the topic stems from a semester abroad in  Denmark where I had the chance to experience the crisis from a European perspective. Over the course of this past semester, the economics department at DIS arranged academic visit to economic think tanks such as Brugel, the European Union Parliament, The OECD, The Banque de France, and Danmark’s Nationalbank. At each visit, the topic of Europe’s debt crisis was a recurring theme. Interestingly, each center had a different perspective on the crisis, but most importantly offered different solutions.

What I strive to understand is what forces cause sovereign debt to become a burden and how these debt ridden nations affect other members of the monetary union. By looking at several macroeconomic data such as Gross Domestic Product (GDP) and focusing on debt-to-GDP and debt per capita, I believe I will be able to discover which nations in Europe are over in-debited. Other important factors which will most certainly affect the severity of the crisis and how it will affect other members include 1)Industrial Production 2)Unemployment 3)Short & Long Term Interest Rates 4) Current Account Balances and 5) Inflation.

For my research to be as accurate as possible, I will be deriving data from large statistical databases such as the Federal Reserve Economic Data (FRED), The European Central Bank (ECB), and each country’s respective central bank (ie: The Bank of Greece, Banco De Espana). All of these databases have up-to-date statistical information which will give me access to time series data prior to the financial crisis through today. Currently I have data mainly from FRED and ECB publications which summarizes principal financial indicators.

FRED Publication:

ECB Publication: