Tag Archive: base effects

Just The One More Boom Month For IP

The calendar last month hadn’t yet run out on US Industrial Production as it had for US Retail Sales. The hurricane interruption of 2017 for industry unlike consumer spending extended into last September. Therefore, the base comparison for 2018 is against that artificial low. As such, US IP rose by 5.1% year-over-year last month. That’s the largest gain since 2010.

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China Prices Include Lots of Base Effect, Still Undershoots

By far, the easiest to answer for today’s inflation/boom trifecta is China’s CPI. At 2.9% in February 2018, that’s the closest it has come to the government’s definition of price stability (3%) since October 2013. That, in the mainstream, demands the description “hot” if not “sizzling” even though it still undershoots. The primary reason behind the seeming acceleration was a more intense move in food prices.

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Commodity and Oil Prices: Staying Suck

The rebound in commodity prices is not difficult to understand, perhaps even sympathize with. With everything so depressed early last year, if it turned out to be no big deal in the end then there was a killing to be made. That’s what markets are supposed to do, entice those with liquidity to buy when there is blood in the streets. And if those speculators turn out to be wrong, then we are all much the wiser for their pain.

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U.S. CPI after the energy push

The Consumer Price Index for January 2017 rose 2.5%, pulled upward by its energy component which thanks to oil prices now being comparing to the absolutely lows last year saw that part of the index rise 11.1% year-over-year. Given that oil prices bottomed out on February 11, 2016, this is the last month where oil prices and thus energy inflation will be at its most extreme (except, of course, should WTI actually rise between now and the end of...

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No China Trade Interpretations

The National Bureau of Statistics (NBS) of China does not publish any of the big three data series (Industrial Production, Retail Sales, Fixed Asset Investment) for the month of January. It combines January data with February data because of the large distortions caused by Lunar New Year holidays.

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