Used this for my presentation yesterday. Credit to Ethan Pollack for pulling much of this together.
Aside from the near-term cuts in the debt deal, there is a broader failure in the proposed package to address jobs. Unemployment is over 9% and will average over 8% in 2012 according to the blue-chip consensus forecast.
In particular, the debt deal did not include a continuation of the payroll tax holiday and extended unemployment insurance (UI) benefits – both of which were part of the December 2010 tax deal, and which will expire at the end of the year.
A quick analysis shows the overall impact (Table 1). (Multipliers from Zandi; jobs derived from historical relationship between GDP and employment). In total, failing to include these policies, plus the cuts, will lead to 1.8 million fewer jobs in 2012.
Link to EPI analysis TK.
See also New Economic Times.
Sent from mobile.
Sent from mobile.
Here is the data from Crain and Crain used to replicate:
This is the STATA data file. Short description is below.
*Short description of variables in STATA file.
With variable labels most variables are self explanatory. Here are a few that might warrant a description: countrynum This assigns a unique integer to each country, range is [0,30]. empty Identifies observations for which all data is complete. Data takes 0 if the observation has complete data or 1 if observation has any missing data.Note: This variable only applies to the original Crain & crain data. It was not updated for the new education variables.
emptyco Identifies the five countries omitted countries from the Crain & Crain regression. Takes 1 if one of the five countries; else 0. Below are the additional school variables we have added in. If you just want the original C&C data, disregard and/or drop these variables. school primary school enrollment, % gross lnschool_enrol natural log of school variable. lnschool_enrol = ln(school) com_upd primary school completion. This is an update of of C&C's education variable and has data through 2008. lncom_upd natural log of com_upd variable. lncom_upd Finally, if you just want the original data given to us by Crain & Crain [NOTE: data was provided by Crain and Crain to a third party, which we then obtained] without any of our created variables, just KEEP the following;
country
code
year
GDP
trade
regulation
population
broadband
education