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Empire State Manufacturing Survey
The monthly survey of manufacturers in New York State conducted by the Federal Reserve Bank of New York.

Survey Indicators
Seasonally Adjusted


Download the full write-up, including the supplemental report and all charts and tables. pdf

The May 2013 Empire State Manufacturing Survey indicates that conditions for New York manufacturers declined marginally. The general business conditions index fell four points to -1.4, its first negative reading since January. The new orders index also edged into negative territory, and the shipments index fell to zero. The prices paid index declined eight points to 20.5, indicating a slowdown in selling price increases, while the prices received index was little changed at 4.6. Employment indexes were mixed, showing both a modest increase in the number of employees and a slight decline in the length of the average workweek. Indexes for the six-month outlook were generally lower, suggesting that optimism about future conditions had weakened.

In a series of supplementary survey questions, firms were asked about past and expected changes in both the prices they paid for inputs and the prices they charged their customers. The same questions had previously been asked in surveys conducted in May 2012 and in May of earlier years. In the current survey, respondents, on average, expected the prices they paid to climb by 2.8 percent—the smallest anticipated rise since May 2009. Moreover, the average respondent anticipated an increase of just 1.2 percent in prices received—the smallest expected increase recorded since these questions were first asked in May 2007.

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Released at 8:30 a.m.

2013
JAN
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APR
15 report PDF
15 report PDF
15 report PDF
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MAY
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15 report PDF
17
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SEP
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16
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Historical Reports ››



Charts of diffusion indexes (past 12 months) PDF

Historical Tables

Diffusion Indexes
Seasonally adjusted: txt | csv
Not seasonally adjusted: txt | csv
Data definitions PDF 2 pages / 10 kb

All Data
Seasonally adjusted: txt | csv
Not seasonally adjusted: txt | csv
Data definitions PDF 2 pages / 10 kb
Seasonal Factors
Seasonal factors: txt | csv
Data definitions PDF 2 pages / 15 kb




Participants from across the state in a variety of industries respond to a questionnaire and report the change in a variety of indicators from the previous month. Respondents also state the likely direction of these same indicators six months ahead. April 2002 is the first report, although survey data date back to July 2001.

The survey is sent on the first day of each month to the same pool of about 200 manufacturing executives in New York State, typically the president or CEO. About 100 responses are received. Most are completed by the tenth, although surveys are accepted until the fifteenth.

For demonstration only:
Sample survey PDF 1 page / 44 kb

Respondents come from a wide range of industries from across the New York State. No one industry dominates the respondent pool.

The survey's main index, general business conditions, is not a weighted average of other indicators—it is a distinct question posed on the survey. Each index is seasonally adjusted when stable seasonality is detected.

Revisions
Each January, all data undergo a benchmark revision to reflect new seasonal factors.

Seasonal Adjustment
The Empire State Manufacturing Survey seasonally adjusts data based on the Census X-12 additive procedure utilizing a logistic transformation.

The "increase" and "decrease" percentage components of the diffusion indexes are each tested for seasonality separately and adjusted accordingly if such patterns exist. If no seasonality is detected, the component is left unadjusted. The "no change" component contains the residual, computed by subtracting the (adjusted) increase and decrease from 100. Seasonal factors are forecast in December for the upcoming year.

Data are adjusted using a logistic transformation. The not-seasonally adjusted series, expressed in decimal form (referred to as "p"), is transformed using the following equation:

X = log(p/(1-p))

The seasonal factor is then subtracted from X:

adjX = X - seasonal factor

The result is then transformed using the following equation:

SA Series = exponential(adjX)/(1+exponential(adjX))

Seasonal factors are available here


Data definitions PDF 2 pages / 15 kb

Contacts
Tech help: nyrsf.webteam@ny.frb.org

Questions about survey/data: richard.deitz@ny.frb.org or (716) 849-5025; jason.bram@ny.frb.org or (212) 720-5651


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