Final Blog Post

Freakonomics Chapter 4

            I find it incredible how states with high abortion rates can take responsibility for a 30% drop in crime relative to States with low abortion rates. I believe I have heard this fact before, therefore I was not completely surprised. In a sociology class I had this summer we talked about how New York City’s fall in crime rate can be mostly attributed to an increase in abortions and birth control, in contrast to the popular belief that Rudy Guiliani’s tough stand on petty crimes was the reason. That being said I would like to know if those particular State’s with high abortion rates also had a high rate of men and women practicing safe sex.

            I like how the book goes into the relationship between mothers and their unwanted children. It seems the family dynamic clearly plays a large role in what a child accomplishes later in life and that high abortion rates may signify what the demographics of an area may be like. “Women who were likely to have abortions were often unmarried, or in their teens, or poor. One study shows that the typical child who went unborn in the earliest years of legalized abortion would have been 50 percent more likely than average to live in poverty; he would have also been 60 percent more likely to grow up with just one parent. These two factors—childhood poverty and a single-parent household—are among the strongest predictors that a child will have a criminal future.”

            I found both additional readings on abortion and crime interesting in the fact that they found opposing results. After spending the past semester working on my paper I can better understand how regressions can come across different answers for the same question. It becomes how you are able to argue the answers you received and whether theoretically the answer you have makes sense. Coming to my own conclusions on the topic I felt that the Levitt and Freakonomics came to the more accurate conclusions. I say this based on the readings as well as past classes that looked at this relationship.

-Stinson out

 

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Too Big to Fail- try this again

            Too Big to Fail is a very well made and very Hollywood version of the start of the 2008 financial crisis and the meltdown of Lehman Brothers. I say that it is very Hollywood because it is not made in a typical documentary style like one would expect, instead it is made like a plot line using actors like Topher Grace. It is an incredibly interesting movie because it highlights some possible motivations for the major players at the time like Bernanke, Geithner, Fuld, Paulson and Buffet. One part I find very interesting is how the portray the role of Richard Fuld, the CEO of Lehman Brothers at the time. Throughout the beginning of the movie you see his disbelief at what was happening and extreme denial, pushing him to think that “the housing market will bounce back” even while his company was losing significant share value at the time. Another aspect I enjoyed about the movie is how they portrayed the other CEO’s of the investment banks as well as the other major banks like Wells Fargo and Bank of America. I felt that showing the personality and “pride” of each of these individuals is an important part of the crisis and what Paulson had to overcome. The reason I do not enjoy the movie is first we all know how it’s going to end so the climax is somewhat underplayed and second it highlights some of the ugliness of the relationship between our private sector and the politics of our country. It is seemingly a severe mistrust, which cannot totally be unforeseen though.

            Overall, although I really do enjoy Too Big to Fail as a movie I think there are a few much better movies that portray the financial crisis much better. First is Inside Job, another documentary the economics department offered as a movie opportunity my sophomore year, and the next is a 4-part PBS documentary that just came out this summer. Both of these do a great job of really looking at the nitty-gritty detail of what happened during the crisis and how did we get to that point. Something that Too Big to Fail does not go to in depth on. Finally, a last thought and something I talked about in my other economics class in monetary policy is, What would have happened if Bear Sterns was allowed to fail instead of being bailed out? Would have the markets acted the same, just acted months earlier, or would have investment banks and other banks realized that they needed to find some answers and acted more appropriately? 

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Too Big to Fail

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Poor Economics Chapter 7

people in poorer nations staggering. “Interest rates vary across sectors and countries, but the bottom line is always the same: Yearly interest rates in the 40 to 200 percent range (or even higher) are the norm.” This statistic is extremely sad and shows insight into how the poor people of a country are unable to lift themselves from their social positions. Interest rates of this magnitude clearly take a large portion of an already minimal profit margin that they are working with. Further, wealthier nations like the United States do not deal nearly with interest rates this high. In fact, 30-year mortgage rates are currently at historic lows of around 3.5% and even credit card interest is around 15-20%, only half of what we see in these poor communities. After presenting this problem I think the book poses the exact right question: why does the market place not offer better opportunities for the poor? Any economics major would justly think that the market will always produce the most efficient solution, but why is that solution found at 40-200% annually? Even the informal economy should have found a way to bring these rates down or the formal economy (banks) should have found a solution to capitalizing on such a large base. Here is a list of reasons that the book used to explain high loans for the poor.

  • Low collateral means smaller loans and a higher potential for the borrower to renege on the loan= higher interest.
  • The lender’s time spent on making sure the loan is being spent for its original purchase instead of in unruly ways. Time is money= higher interest.
  • Multiplier effect, as the loan goes up the borrower has more reason to try and not repay it, meaning monitoring and screening increases. The upward pressure feeds on itself and interest skyrocket, or the lender may believe the loan is so small that it is not worthwhile.

It seems that the emphasis on contract enforcement is what really drives a loans interest up. As they say in the book, “the high costs of collecting information on a borrower also help explain why even when there are several moneylenders in each village, competition does not drive the price of credit down.” After knowing these facts it becomes much easier to see why richer nations and wealthier people are able to benefit from lower interest rates.

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Fiscal Cliff

The “Fiscal Cliff” that is supposed to take effect as of January 2013 was a major driver for in choosing my topic and is also all over the news as of recently. I was originally interested in researching Fiscal Spending in order to gain a better understanding of what these future tax hikes and spending cuts could affect our economy. Since there is usually a new article about the fiscal cliff most days in significant newspapers I had plenty of choices. An article I found online by Mark Jewell of the Miami Herald specifically caught my eye. Jewell mentions the different sort of tax increases that we will be experiencing in the future. In other words, the end of the Busch-tax cuts. I would have liked this article to talk more about what spending cuts the economy would be experiencing, but those were also not brought up. He did not necessarily mention anything that would be helpful for my data in regressions, instead he looked at the potential impact the fiscal cliff would have on the market and possible investors. This is certainly important information though as it may point towards future spending habits of consumers and whether they are looking to withdraw from the market in fear of a double-dip recession. This article has provided me with insight that I can certainly apply in either the introduction of my paper or during my discussion. As of right now I am still unsure about what my regression will tell me about fiscal spending but from the literature I have read it would seem it should have a positive effect on employment in a state. Overall, I was hoping this article would provide me with more details on the fiscal cliff and the exact expenditures that are being cut. Most of the articles that I have read point out that some types of government spending are more effective than others. Tax cuts on the other hand are somewhat irrelevant to my paper and what I am looking at.

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State Fiscal Spending Academic Article

One of the most helpful papers that I have been looking at was written by economists Gabriel Chodorow-Reich, Laura Feiveson, Zachary Liscow and William Gui Woolston. The paper asks the above question and looks at evidence from the American Recovery and Reinvestment Act (ARRA). It is a fairly recent paper that came out in August 2011 which tells me that it is directly applicable to my topic.

What has been the most helpful about this paper is that it has given me multiple variables that I should think about including in my model. In particular multiple control variables that I did not think of including before such as a variable for pre-existing economic conditions, GDP per potential worer and only looking at the non-institutional working population 16+. These and more are all variables that I did not think of including in my first regression. Further it has also given me the idea of looking at changes in levels of employment instead of looking at the unemployment level. Although this may sound like a small change I can assure you that it is not and should make a big difference in my model. Luckily this paper has also directed me to sites where I can find this data which saves me a bunch of time data searching.

The paper runs multiple regressions using different control variables in order to get the best reading possible of the data. It fails to mention whether they put these variables in the functional form or linear form but talks about a bivariate regression. The authors did run robustness tests (or in one section call them falsification tests), but does not suggest any violations in the model. I’ll be interested to gather the proper data for my years and see how the regressions compare.

Chodorow-Reich, G. (2012). Does State Fiscal Relief during Recessions Increase Employment? Evidence from the American Recovery and Reinvestment Act. American Economic Journal, 4(3). Retrieved September 27, 2012, from http://www.libproxy.wvu.edu

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 1.     …

 

  1. 1.       Introduction
    1. a.       The GDP of an economy is made up of private consumption, gross investment, government spending , and net exports. Healthy GDP growth is helpful in determining many macro indicators like unemployment. In the United States in particular if GDP continually grows near  4-5% a year the country should eventually reach a level known as full employment. All GDP factors contribute in reaching this goal, but it is unclear how big of a factor each one may have. This study will particularly look at the effects that state spending during fiscal year 2010 had on the states’ particular unemployment rate. It will look to see whether or not high levels of spending are associated with lower unemployment, or if crowding out occurs and negates the potential benefits of that spending. As a post-recession year, fiscal 2010 will be a particularly interesting year to examine. The country at this point continued to suffer from a high unemployment rate with high levels of spending state-wide. Since this time period the nation has continued to grow but has struggled in gaining momentum and control of the job market. With a looming fiscal cliff in January 2013 this paper will highlight how much of an impact government spending or in particular, state spending, really has on the labor market. In the next section I will describe the findings of other economists that have touched upon this section. I will describe their approach to solving this question and what they determined. In section three I will use my developed model to analyze this question from an angle different than my above peers. In section four I will discuss the data collected to test my hypothesis, and in section five I will use that data with my theory as evidence for my question. Finally, I will conclude my findings and the errors that may have occurred.
    2. 2.       Literature Review
      1. Article 1: Deficits, full employment and the use of fiscal policy

                                                               i.      By Steven Pressman

                                                             ii.      This paper argues that neither theoretical nor empirical support exists to say that fiscal policy is incapable of solving the unemployment problem because  government deficits crowd out consumer spending, business investment and net exports

  1. Article 2: Government Spending and Private Activity

                                                               i.      By Valerie A. Ramey

                                                             ii.      This paper studies several aspects of the labor market to see the effects of government spending shocks on unemployment. It determines that government spending does not stimulate private spending; most estimates suggesting that it significantly lowers private spending.

  1. Article 3: Does state fiscal relief during recessions increase employment? Evidence from the American Recovery and Reinvestment Act (ARRA)

                                                               i.      By Gabriel Chodorow-Reich, Laura Feiveson, Zachary Liscow, William Gui Woolston

                                                             ii.      This paper examines the effect of ARRA on states’ employment. The study determines an additional 3.8 job-years, 3.2 of which are outside the government, health and education sector

 

 

 

 

 

  1. Data
 

Fiscal 2010

State

General Fund

Federal Funds

Other State Funds

Bonds

Total

Alabama

6,588

8,692

4,913

391

20,584

Alaska

5,626

2,925

1,208

0

9,759

Arizona

9,079

10,655

6,891

1,055

27,680

Arkansas

4,223

6,894

8,716

89

19,922

California

87,237

89,088

23,514

6,250

206,089

Colorado

7,326

9,223

14,515

0

31,064

Connecticut

$11,851

$2,567

$3,457

$1,819

$19,694

Delaware

3,077

1,607

3,783

253

8,720

Florida

21,216

22,763

16,725

1,345

62,049

Georgia

14,575

14,647

10,058

1,161

40,441

Hawaii

4,838

2,391

3,045

674

10,948

Idaho

2,338

2,573

1,455

27

6,393

Illinois

26,301

16,050

17,410

892

60,653

Indiana

12,915

10,333

3,245

169

26,662

Iowa

5,302

6,174

6,050

111

17,637

Kansas

5,269

5,188

3,270

318

14,045

Kentucky

8,450

10,477

7,014

0

25,941

Louisiana

9,061

11,859

7,573

641

29,134

Maine

2,866

3,151

2,159

81

8,257

Maryland

13,442

9,825

8,766

1,071

33,104

Massachusetts

27,582

3,932

17,037

1,873

50,424

Michigan

7,696

19,541

20,254

267

47,758

Minnesota

15,425

9,389

4,573

746

30,133

Mississippi

4,278

8,731

4,855

419

18,283

Missouri

7,565

10,919

6,330

712

25,526

Montana

1,628

2,285

2,136

0

6,049

Nebraska

3,313

2,973

3,320

0

9,606

Nevada

3,050

2,792

2,318

124

8,284

NewHampshire

1,380

2,072

1,876

138

5,466

NewJersey

28,926

13,687

3,482

1,669

47,764

NewMexico

5,258

5,429

3,953

606

15,246

NewYork

54,262

40,834

30,578

3,263

128,937

NorthCarolina

18,512

17,162

12,583

488

48,745

NorthDakota

1,585

1,852

1,388

20

4,845

Ohio

25,412

14,236

16,864

1,128

57,640

Oklahoma

6,225

10,362

4,455

565

21,607

Oregon

6,371

8,378

17,336

469

32,554

Pennsylvania

24,942

27,669

13,842

1,655

68,108

RhodeIsland

2,864

2,813

2,032

101

7,810

SouthCarolina

5,146

7,691

7,380

85

20,302

SouthDakota

1,132

1,729

892

67

3,820

Tennessee

9,914

12,951

5,484

100

28,449

Texas

39,465

36,672

15,924

1,060

93,121

Utah

4,441

3,607

4,550

2,393

14,991

Vermont

774

1,865

1,954

74

4,667

Virginia

14,989

9,327

15,001

1,456

40,773

Washington

15,036

9,238

7,284

2,029

33,587

WestVirginia

3,682

4,475

12,122

77

20,356

Wisconsin

12,824

11,532

15,730

0

40,086

Wyoming

3,836

1,430

2,391

0

7,657

Total

$619,093

$552,655

$411,691

$37,931

$1,621,370

 

 

 

 

 

 

 

State

Population (1,000)

 Population per square mile of land area \1

2010 Unemployment Rate

2010 Per Capita State Expenditures

 

Alabama

4,780

94.4

9.5

$4,306.51

 

Alaska

710

1.2

8

$13,740.60

 

Arizona

6,392

56.3

10.5

$4,330.40

 

Arkansas

2,916

56.0

7.9

$6,832.15

 

California

37,254

239.1

12.4

$5,532.00

 

Colorado

5,029

48.5

8.9

$6,176.73

 

Connecticut

3,574

738.1

9.3

$5,510.20

 

Delaware

898

460.8

8

$9,711.18

 

Florida

18,801

350.6

11.3

$3,300.25

 

Georgia

9,688

168.4

10.2

$4,174.49

 

Hawaii

1,360

211.8

6.9

$8,048.22

 

Idaho

1,568

19.0

8.8

$4,078.26

 

Illinois

12,831

231.1

10.5

$4,727.20

 

Indiana

6,484

181.0

10.1

$4,112.09

 

Iowa

3,046

54.5

6.3

$5,789.54

 

Kansas

2,853

34.9

7.2

$4,922.68

 

Kentucky

4,339

109.9

10.2

$5,978.06

 

Louisiana

4,533

104.9

7.5

$6,426.56

 

Maine

1,328

43.1

8.2

$6,419.19

 

Maryland

5,774

594.8

7.8

$5,733.73

 

Massachusetts

6,548

839.4

8.3

$7,701.11

 

Michigan

9,884

174.8

12.7

$4,832.03

 

Minnesota

5,304

66.6

7.3

$5,681.26

 

Mississippi

2,967

63.2

10.5

$6,161.50

 

Missouri

5,989

87.1

9.4

$4,262.20

 

Montana

989

6.8

6.9

$6,113.71

 

Nebraska

1,826

23.8

4.7

$4,535.85

 

Nevada

2,701

24.6

13.7

$2,024.03

 

New Hampshire

1,316

147.0

6.1

$36,281.88

 

New Jersey

8,792

1,195.5

9.6

$1,734.10

 

New Mexico

2,059

17.0

7.9

$62,615.73

 

New York

19,378

411.2

8.6

$495.71

 

North Carolina

9,535

196.1

10.9

$5,111.96

 

North Dakota

673

9.7

3.8

$7,203.49

 

Ohio

11,537

282.3

10

$4,996.31

 

Oklahoma

3,751

54.7

6.9

$5,759.79

 

Oregon

3,831

39.9

10.7

$8,497.36

 

Pennsylvania

12,702

283.9

8.5

$5,361.83

 

Rhode Island

1,053

1,018.1

11.7

$7,419.96

 

South Carolina

4,625

153.9

11.2

$4,389.28

 

South Dakota

814

10.7

5

$4,691.84

 

Tennessee

6,346

153.9

9.8

$4,482.91

 

Texas

25,146

96.3

8.2

$3,703.28

 

Utah

2,764

33.6

8

$5,423.89

 

Vermont

626

67.9

6.4

$7,458.36

 

Virginia

8,001

202.6

6.9

$5,095.97

 

Washington

6,725

101.2

9.9

$4,994.69

 

West Virginia

1,853

77.1

8.5

$10,985.46

 

Wisconsin

5,687

105.0

8.5

$7,048.72

 

Wyoming

564

5.8

7

$13,585.25

 

                     

 

  1. 4.       Methodology
    1. a.       2010 State Unemployment= General Fund+ Federal Fund+ Other State Funds+ Bonds+ Population State Density+ Per Capita State Expenditures

                                                              i.      Although this is a working formula and far from perfect I am still determining whether total state expenditures does justice for the formula, or if each piece of state expenditures is integral. Further although I believe population density may capture how urban a state is I still need to determine a good variable for private expenditure. Maybe using home mortgages to measure investment and consumption per state would be the best solution. Any recommendations for this part of my equation would be much appreciated.

                                                            ii.       Also I have read differing opinions on politics in a state and spending, would it be wise to include a dummy variable for republican, democrat or independent government?

                                                          iii.      Finally is per capita state expenditure needed or can it be omitted? I felt that it would help define unemployment better.

  1. 5.       Determining my Solution
    1. a.       I believe my results will show me that state government spending does not make a significant impact on the unemployment rate. Our current economy is built on the private sector and the largest growth comes from there. Although it may make some impact with jobs I think crowding out may become a larger variable that I am expecting.
    2. 6.       Conclusion
      1. a.       My conclusion will sum up all my research and look at ways that this study can be improved. Whether it is variables I was unable to determine or data that was not perfect I will state ways other researchers can go about this study to determine a more accurate answer.
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