The Kansas Economy: Three Pictures

The Philadelphia Fed released coincident indices today. Figure 1 shows state-by-state 3 month trends. Needless to say, the outlook for Kansas — that laboratory for supply side nostrums — is not auspicious.

coincident2016-09

Source: Philadelphia Fed, accessed 26 Oct 2016.

While Alaska seems to be in the running for worst performing, in fact the 3 month (annualized) decline of 4.5% for Kansas is the worst in the 50 states.

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The Mexican Peso and Prediction Markets

I was talking about prediction markets and asset prices (the Mexican peso and the Presidential election, and the pound and Brexit) in my classes this week. It struck me a good time to update this post on the peso’s movements as the odds for a Democratic win change.

election_mxn4

Figure 1: USD/MXN exchange rate (blue), and odds of Democratic win in Presidential election, end of day (red). Observation for 10/20/2016 is as of 2:30PM Eastern time. Exchange rate defined so up is MXN appreciation. Source: FRED, Pacific Exchange Services, and Iowa Election Markets.

The adjusted R2 of a bivariate regression of first differences regression (exchange rate in logs) is 0.08, pretty good on a high frequency time series, in my book (t-stat with HAC robust errors is 2.06).

Global Temperature Anomaly, Through September

globanom_sep16

Source: NOAA

The highest point estimate for the anomaly is for 2016. For 2014, the 95% interval is ±0.09°C [1]. If that is ballpark for the 9 months estimate, then one can’t say that 2016 is hotter than 2015 (with statistical significance at the 5% msl), but can say it is hotter than 1998, a year often focused on by the “hiatus”-ers.

Update, 5:08PM Pacific: Here is a trailing 60 month moving average, ending observation for September 2016.

globanom_sep16_60momovav

Source: NOAA

The Jordà-Schularick-Taylor Macrohistory Database, Online

One of the problems in conducting cross-country analyses of infrequent macroeconomic episodes (such as financial crises) is absence of a comprehensive historical dataset. That has been partly remedied by the publication of the Macrohistory Database, assembled by Oscar Jordà, Moritz Schularick, and Alan Taylor (see the paper utilizing this database, discussed here by Jim).

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