A Critique of "The Impact of Legalized Abortion on Crime"

After reading the critique of "The Impact of Legalized Abortion on Crime" I would have to side with the authors of the critique. It is however possible that Donohue and Levitt came out with a response to the critique arguing their side. But several factors impact my assessment of the original paper. As the critique points out, there was a coding mistake in DL's concluding regressions, which identified abortion's effect on crime by comparing the experiences of different age cohorts within the same state. Another convincing theoretical argument is that statewide crime rates are influenced by other factors besides abortion, and that crime in one state is not necessarily caused by the same crime committed in another state. The final nail in coffin in my mind comes from the fact that DL's final regression uses total number of arrests instead of per capita number of arrests. This would certainly distort the regression results and would incorrectly measure abortion's effect on crime.

Finance Symposium

The topic of today's finance symposium was finance reform. I had the opportunity to ask a question and asked whether the Citizens United ruling had any effect on the increase in money spent during the general election. The increase in money spent between 2008 and 2012 on general elections (according to numbers from the Center for Responsible Politics) was approximately 18.9%. The speaker responded that this number was slightly above the historic average and could possibly be attributed to the Citizens United ruling. Another question that I wanted to ask but didn't get the chance to was whether the speakers expect that number to remain static in the future or to increase. If the increase in money spent was accounted for by the $1 billion of outside money, I would not expect the percent change to increase in the future. But if large donors become more accustomed to the new campaign finance laws and learn how to work within them, I would expect this number to increase in the future.

Another question I had was whether the amount of money spent was in nominal or real terms. If the numbers were in nominal terms, using real dollars would shrink the percent increase from one election to another. However I'm still convinced that the percentage increase would be considerably large. It would also be interesting to compare the increase in amount of money spent to several inflation statistics such as the CPI, PCE, and PPI indexes. I am confident that the percentage increase in money spent during elections would outpace inflation statistics. I'm not sure what this means for results of elections or the economy as a whole, I just find that comparison interesting.

“Reassessing Discretionary Fiscal Policy”

In paper he wrote in 2000, John Taylor of Stanford University wrote about why discretionary fiscal policy is a bad macroeconomic tool. He argues that the overall size of the changes in taxes and spending due to automatic stabilizers are usually larger the discretionary fiscal policy proposals. He also argues that automatic stabilizers are more predictable and work more quickly that discretionary fiscal policy.

I could analyze both discretionary fiscal policy and automatic stabilizers separately, but my main focus is on total credit marked debt owed, which includes both automatic stabilizers and discretionary fiscal policy. Unfortunately, this paper does not include econometric analysis and only relies on theoretical arguments. I did find another paper though that analyzed both automatic stabilizers and discretionary spending and their effects on industry growth using econometric analysis. Their models give me some good ideas on how to develop the right functional form for my model

Taylor, John B. 2000. “Reassessing Discretionary Fiscal Policy,” Journal of Economic Perspectives. 14:3 pp. 21-36

Fingers on the Scales

The scene from Margin Call that had the most powerful effect on me was Will Emerson's monologue on "normal people." In this scene he dodges the claim that bankers were the ones that caused the crisis and instead put the blame on "normal people" for wanting big cars and big houses that they could not afford. This is partially true as the subprime mortgage crisis was a very large contributor to the financial crisis in 2008 (however we do also hear of predatory practices pursued by lenders).

The years after the crisis have been spent by consumers deleveraging the debt that they had accumulated and the process is almost completed. However this begs the question of whether consumers will "releverage". Many economists argue that despite the reforms enacted following the 2008 crisis dangers still exist within the financial system, namely that banks are still "too big to fail" or "too big to regulate". This begs the question of whether the government will ball out the banks again if another crisis were to strike.

Are we destined for another financial crisis? Is the Dodd-Frank bill really sufficient to protect the financial system? Are banks still "to big to fail" or "to big to regulate"? Hopefully the answers are no, yes, and no. Unfortunately, only time will tell.

Preliminary Regression

According to the quantity theory of credit, credit multiplied by the turnover rate of credit is equal to nominal gdp, growth in the total stock of credit should lead to a growth in nominal gdp (this is the relationship of interest in my regression). Regressing log(GDP)(nominal gdp growth) on log(TCMDO)(total credit market debt owed growth) gives the following results:

Dependent Variable: LOG(GDP)
Method: Least Squares
Date: 03/21/13   Time: 14:54
Sample (adjusted): 1968Q1 2012Q4
Included observations: 180 after adjustments
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	1.636129	0.038789	42.17971	0.0000
LOG(TCMDO)	0.738261	0.004144	178.1325	0.0000
R-squared	0.994422	Mean dependent var		8.491701
Adjusted R-squared	0.994390	S.D. dependent var		0.867738
S.E. of regression	0.064992	Akaike info criterion		-2.618068
Sum squared resid	0.751856	Schwarz criterion		-2.582591
Log likelihood	237.6261	Hannan-Quinn criter.		-2.603684
F-statistic	31731.18	Durbin-Watson stat		0.019569
Prob(F-statistic)	0.000000

According to this regression, a 1% increase in TCMDO is correlated to .74% growth in GDP. However there are problems with this regression. The Durbin-Watson statistic indicates that there is a high level of autocorrelation in this model. This could be solved for by adding a first and second order autoregressive scheme. If the t value for LOG(TCMDO) is still significant and a Breusch-Godfrey serial correlation test indicates that there is no autocorrelation, then we cannot reject the hypothesis that there is no autocorrelation in the model.

Though it must be noted that this model does not prove causality, only correlation. It could be that credit growth drives GDP growth or that GDP growth drives credit growth. Causality is beyond the scope of this model.

Top of the Class

One of the topics covered by the authors of Poor Economics in their chapter on education was how to "nudge" families to send their children to school. Governments in developing countries offered conditional cash transfers to families if they sent their children to school. The results were outstanding, with secondary school enrollment increasing from 67% to about 75% for girls, and from 73% to about 77% for boys.

The Economist published a great article last March on the use of behavioral economics in public policy. In one experiment researchers painted footsteps on the ground in patterns that went past trash cans. The result was a reduction in littering by 46%. If governments can effectively harness the uses of behavioral economics, it could certainly lead to better economic outcomes.

Research Abstract

Monetarists believe that the state of the economy can be explained by the quantity theory of money,  MV=PY. However the quantity theory of credit, MC=PY has received much less attention. This paper seeks to describe the relationship between the stock of credit in the national economy and GDP. Implications for fiscal policy regarding federal government debt and private sector debt is then analyzed.

References

Taylor, John B. 2000. “Reassessing Discretionary Fiscal Policy,” Journal of Economic Perspectives. 14:3 pp. 21-36.

Cochrane, John H. 2011. “Understanding Policy in the Great Recession: Some Unpleasant Fiscal Arithmetic,” European Economic Review. 55. Pp. 2-30.

Martin, Philippe and Carol Ann Rogers. 1997. “Stabilization Policy, Learning-by-Doing, and Economic Growth,” Oxford Economic Papers. 49. Pp.152-166.

Calderon, Cesar, Roberto Duncan and Klaus Schmidt-Hebbel. 2004. “Institutions and cyclical properties of macroeconomic policies,” Central Bank of Chile Working Paper Number 265.

Gale, William G. and Peter R. Orszag. 2003. “The Economic Effects of Long-term Fiscal Discipline,” The Urban-Brookings Tax Policy Center Discussion Paper Number 8.

Aghion, Philippe and Enisse Kharroubi. 2007. “Cyclical Macro Policy and Industry Growth: The Effect of Counter-cyclical Fiscal Policy,” Banque de France Paper Number ?.