Martha Starr-McCluer

Who they are

This page records the public professional record only. Nothing adverse is recorded and no motive is attributed.

Her paper appears in the Finance and Economics Discussion Series of the Board of Governors of the Federal Reserve System. Her wider career was not verified for this page, so none is asserted here. The record used is one paper, and it was read at the level of its published abstract.

Key papers

Starr-McCluer, M. (2000), 'The Effects of Weather on Retail Sales', Finance and Economics Discussion Series 2000-8, Board of Governors of the Federal Reserve System. Read at the level of the published abstract.

Her wider publication record was not surveyed for this page.

Key ideas

The paper starts from the common view that monthly swings in consumer spending are caused by the weather, and tests it. Its model treats weather as a change in how productive people's time is for activities outside work, such as shopping or recreation. Through time and budget constraints, that can shift spending among goods and across periods.

Using monthly retail sales and National Weather Service data, the author found that unusual weather had a modest but significant effect on monthly sales fluctuations. Lagged effects often offset the initial effects, so the influence largely disappeared at a quarterly frequency. That is the empirical core of demand displacement.

The abstract gives no figure for the size of the effect, so none is printed here. The result concerns American aggregate retail sales in monthly data, which is a different object from the daily store-level data in the later studies, and the two should not be set against each other as if they measured the same thing. Her result is the basis for the caution in What a Weather Forecast Does for Sales that a weather lift in one week may be paid back over the following ones.

How to read the result

The paper's starting point is a belief, not a finding: that the weather explains a good deal of the month-to-month swings in retail spending. Testing it meant asking what weather would do to spending in theory. Her answer treats weather as a change in how productive people's time is for shopping and recreation. If a pleasant weekend makes outdoor time more valuable, spending can shift among goods, and if a storm makes shopping costly, the purchase can move to another day. That reasoning is why the paper expects offsets between periods and not only losses.

The empirical result follows the theory. Unusual weather had a modest but significant effect on monthly sales fluctuations, and later months often offset the first effect, so the influence had largely gone when the data were viewed quarterly. A planner reading this should take two things from it. A weather effect on a month is real and measurable. And an order built on it is partly a loan from the following months, which is the point behind demand displacement.

The scale of the data decides how far the result travels. It concerns American retail sales in aggregate and in monthly figures, matched to National Weather Service data. Aggregates can hide what individual stores see, and a month can hide what a day does. That is why later work on daily store sales, such as Brigitte Roth Tran's, is read beside this paper and not as a replacement for it.

What the record does not show

The abstract gives no figure for the size of the effect, so this page prints none. It does not say how the result varies by product category, and the Federal Reserve discussion paper was read at the level of its abstract. Her wider career was not verified for this page, and no institutional detail beyond the paper's series and year is asserted.

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