A collection of JEP articles readers have cited as useful for instruction, by category:
Category Archives: Uncategorized
Mass Shootings and the Trump Effect (Part II)
Casualties (killed, wounded) from mass shootings are not continuously distributed; this suggests an alternative approach — given the high variance (shown in Figure 1 below for a subsample of the data) — I estimate a negative binomial regression (quasi-maximum likelihood).
Mass Shootings and the Trump Effect
Poisson regression, 1982M08-2019M08 (thru 8/4 for August):
eventst = -9.84 + 0.723 trumpt – 0.424 bant + 0.0039 time
Adj-R2 = 0.17, SER = 0.480, NOBS = 445. Bold denotes significant at 10% msl.
Addendum, 8/6 8am Pacific: events is mass shooting event count as defined by Mother Jones tabulation, ban is assault weapons ban dummy, trump is a Trump administration dummy, time is a linear time trend.
Interpretation: Each month of the Trump administration is associated 0.7 more mass shooting events 70% more mass shooting events, so jumping from 0.43 to 0.88 events going from 2016M12 to 2017M01; or approximately 5.4 more events per year 8.4 more events per year. [h/t Rick Stryker for correction of interpretation].
Them’s Fightin’ Words: Futures, Mean Squared Error, Mean Absolute Error
For some reason, my use of commodity futures as predictors of future spot prices for commodities (e.g., soybeans) incites fire and fury from some Econbrowser readers. Hence, I want to cite another example of the use of futures.
“International spillovers of monetary policy through global banks”
That’s the title of a new special issue of the Journal of International Money and Finance, co-edited by Claudia Buch, Matthieu Bussière, Menzie Chinn, Linda Goldberg, Robert Hills, drawing on proceedings from an International Banking Research Network conference. From the introductory paper:
International spillovers of monetary policy have been core topics of theoretical and applied work in recent years, and thesubject of intense discussions in policy circles. Recent literature has improved our knowledge of international policy trans-mission, for instance: by investigating the role of global liquidity conditions; by analyzing international bond price orexchange rate responses to monetary policy decisions using very high frequency data and identification of monetary shocks;and by assessing countries’ monetary policy autonomy by examining the interest rate co-movements with base country pol-icy instruments. Still, gaps in this literature persist. In particular, most of the literature has focused on macroeconomic chan-nels, whereas comparatively less attention has been paid to transmission via banks, which may vary depending on individual banks’ characteristics and the features of national banking systems.
Against this background, the International Banking Research Network (IBRN) launched a project aimed at closing some ofthese gaps, drawing on a unique network of researchers and data. Country teams compiled individual bank-level data for theperiod from 2000 through 2015, usually based on confidential data proprietary to central banks, and then analyzed thosedata using a common empirical method. Small groups of country teams collaborated on papers to bring out instructive com-parisons and contrasts about the way in which monetary policy can have effects across borders via banks.
Recession Indicators as of July 21
Industrial production is down relative to previous month, and relative to recent peak. GDP, sales, personal income are all below recent peak as well. Nonfarm payroll employment continues to plug along — although at a decelerating pace (1.53% y/y).
Exchange Rates: Some Recent Papers
I’ve spent the last week at the NBER’s Summer Institute, attending sessions on International Finance and Macro, International Asset Pricing, and International Trade and Macro (among others)…Here are some interesting/provocative exchange rate papers I saw presented (if off the list, I might’ve missed the paper’s presentation). Other interesting papers in a near-future post.
George Washington and Victory at IAD
Source: Terry Australis
The Trump Administration Is No Friend of the Farmer: Part 15,327
Price index for gross value added in farm sector is falling (cumulative 8% under Trump) while that in the nonfarm business is rising (cumulative 3.5%).
Figure 1: Log price index for gross value added in nonfarm business sector (blue), and farm sector (red), 2017Q1=0. Pink shading denotes period during which China has tariffed US soybeans. Source: BEA 2019Q1 3rd release, authors’ calculations.
