Mining, Manufacturing and Wholesale Trade Division

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Survey Definitions and Instructions
1. Sales
2. Inventories
3. Orders
4. Production Capacity
5. Production Capacity Percentage
Inquiries

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Survey Definitions and Instructions

Reporting Unit: Activities reported should be comparable to those reported to the Annual Survey of Manufacturing and Logging Industries (ASML). If establishments for which individual reports are prepared for the ASML must be combined for this report, list the establishments included or report them to the interviewer. Report any changes in establishment coverage if they occur.

Frequency: Please submit data at the end of each accounting period either by telephone, mail, fax or electronically. For report due date, please refer to the front page of the questionnaire.

Source of Data: Sales and inventory data should be available from monthly statements. Unfilled orders may be maintained separately. When values are not available by the due date, estimates are acceptable. If previously reported values have been revised, kindly note them in the “remarks” section on the monthly report, submit them on a separate sheet of paper or explain the change to the interviewer.

Note: DO NOT include sales tax (provincial, federal or GST), excise duties, excise tax or discounts.

1. Sales

Report only sales for the accounting period. DO NOT report cumulative or year-to-date values.

1. Sales of Goods Manufactured: Sales of goods out of the manufacturing establishment, except to warehouses that are part of the same accounting entity and goods on consignment. In addition to normal sales, include transfers to other establishments in the same company, sales from warehouses that are part of the same establishment, sales of goods shipped earlier on consignment, all sales for which an export permit is prepared, revenue for custom and repair work done, charges for installation where they are part of sales. Also include capitalized value of any goods manufactured by this establishment that have been built for subsequent rental.
2. Sales of goods purchased for resale, as is: Value of sales of goods purchased and resold in the same condition. This category also includes the value of goods purchased in bulk which remain unchanged when resold except for cutting and packaging.
3. Total: Sum of 1(a) and 1(b).

2. Inventories

This section is for reports of the book value of inventory normally held by the establishment. Include: inventory used for long term contracts involving progress billings or payments without adjustment, goods in transit in Canada, goods held in warehouses that are part of the establishment, goods shipped on consignment in Canada until they are sold. Exclude: inventory owned and held abroad, e.g. purchases that have not cleared customs, finished products in foreign warehouses, or on consignment in foreign countries.

1. Inventories of Raw materials, fuel, supplies, components: Include all items bought for processing and assembling that have not been charged out to processing. The value of logs and rough lumber may be reported either here or in goods in process but consistent with reports to the Annual Survey of Manufactures and Logging Industries.
2. Inventories of Goods/Work in process: Report the gross book value before reduction for partial billings or progress payments (in other words payments made as work progresses).
3. Inventories of Finished goods manufactured: Include goods manufactured or processed by the establishment ready for sale.
4. Inventories of Goods purchased for resale, as is: Include items of non-manufacturing inventory in addition to any goods purchased for resale in the same condition except for cutting and packaging.
5. Total inventory: Sum of 2(a), 2(b), 2(c), and 2(d).

3. Orders

For the purpose of this survey, unfilled orders are for goods to be manufactured by the establishment that have not been transferred to sales or treated as a sale. Exclude orders for goods purchased for resale, as is.

Unfilled orders at month end: Report the total value of the unfilled orders less those portions which have been treated as a sale.

4. Production Capacity

This section measures the potential production (production capacity) and the actual production (capacity utilization) of your operations.

Estimate the market value of production of the plant as if it had been operating at full production capability for the whole month.

Assume:

• only machinery and equipment in place and ready to operate
• normal downtime
• labour, materials, utilities, etc. are fully available
• the number of shifts, hours of operation and overtime pay that can be sustained under normal conditions and a realistic work schedule in the long run
• the same product mix as the actual production
• market value of production can be obtained by adjusting the value of shipments with the change in stocks inventories of Goods/Work in process and of finished goods manufactured.

The production value of a given product is calculated using the following formula:

Value of Production = value of sales of goods manufactured plus (+) [closing value of goods and work in process (-) opening value of goods and work in process] plus (+) [closing value of finished goods manufactured (-) opening value of finished goods manufactured]

Prod_t = Sales_t + (GIP_t - GIP_t-1) + (FG_t – FG_t-1)

Cap_Prod = max Prod_{t = t-i,} i = 1, 2…,12

GIP: Good in and or work in process
FGM: Finished Goods manufactured
Cap_Prod: Production Capacity

OPTION 1 – Value (in dollars)

If you report for more than one plant, please determine the production capacity for each plant and provide the sum of these values.

OPTION 2 – Volume and Average Price

Volume

If you report for more than one plant, please determine the production capacity for each plant and provide the sum of these figures.

Average Price

If your plant(s) produce(s) different products, please use a product mix at capacity which is most similar to the composition of your output for this reference period.

5. Production Capacity Percentage

The Production Capacity Percentage is calculated by using the following formula:
Divide your actual production estimate by your full production estimate in question 6 and Multiply this ratio by 100 to get a percentage.

Inquiries

The telephone number for the Statistics Canada Regional Office in your area appears on the enclosed letter or the monthly survey form.

Mailed inquiries may be sent to that Regional Office in the postage-paid envelope that accompanies the survey form or to:

Statistics Canada
Mining, Manufacturing and Wholesale Trade Division
Monthly Survey of Manufacturing Section
Ottawa, Ontario, K1A 0T6

The purpose of this survey is to obtain information to produce national and provincial level estimates of potato production. These estimates will be used by producer organizations, government departments and others.

Confidential when completed. Collected under the authority of the Statistics Act, 1985, Chapter S19.

1. Jun
2. Oct

• Still farming
• No longer farming
• Change of operator
• Produces potatoes
• No longer growing potatoes
• No potatoes this year

If any of the above information is incorrect or missing, please make any necessary corrections below.

• Farm Name (if applicable)
• Surname or Family Name
• Home Phone Number
• Usual First Name and Initial
• Cell Phone Number
• R.R.
• Box No.
• Number and Street Name
• Postal Code
• Post Office (name of city, town or village where mail is received)
• Partner's Name if Applicable
• Partner's Phone Number if Applicable
• Partner's Name if Applicable
• Partner's Phone Number if Applicable
• CORP Corporation Name if Applicable
• Business Phone Number if Applicable

Record of calls (area in June)

• Date
• Time
• Result

Record of calls (yield in October)

• Date
• Time
• Result

Potato area survey 2009

1. Are you growing potatoes for sale this year?

• Yes - go to question 2
• No - complete potato operation status and end interview

2. Is this farming operation a partnership?

• Yes (Update partner information in operator identification section on first page, then proceed to question 4)
• No

Ask question 3 only in June. If calling in fall skip to question 4:

3. What is the total area planted to potatoes in 2009? (Please report for entire operation, area planted to potatoes on land owned or rented by all partners in the operation)

1. Total area planted to potatoes
2. Was the area reported in:
   • acres
   • hectares

End interview here in June

1. Comments

4. What was the total area planted to potatoes in 2009? (Please report for the entire operation, area planted to potatoes on land owned and rented by all partners in the operation).

1. Will the area be reported in:
   • acres
   • hectares
2. Total area planted to potatoes

5. What was the total area of potatoes harvested in 2009?

6. What was the average field run yield for your potatoes? Please report the average yield on the acres harvested, not total area and please report the yield based on product moving into storage, not the marketable yield.

Or

7. What was the total field run production of harvested potatoes?

Please report the production from the entire operation and the production moving into storage, not the marketable production

• Was the yield or production reported in:
  • tons
  • cwts
  • tonnes
  • barrels (165 pounds)
  • other (please note)

8. What percentage of your harvested crop do you expect to make grade?

The percentage that you expect to make grade for table, seed or processing as defined by the grading standard of the Canadian Food Inspection Agency, your provincial grading standards or your processor.

Comments

Agreement to Share Information (N.B., Sask. And B.C. only)

This survey is being conducted under a cooperative agreement between Statistics Canada and your provincial ministry of agriculture.

Do you agree to share this information?

• Yes
• No

This document details the way Statistics Canada calculates trend-cycle estimates. It is intended as a technical document to support users who wish to apply trend-cycle estimation to monthly series available on CANSIM. General formulas outlining the mathematical calculations are presented below, and the derivation and application of the moving average weights are provided. For more information on the use of trend-cycle estimates in analysis, please refer to "Trend-cycle estimates: Frequently asked questions" (Statistics Canada 2015).

The trend-cycle estimation method used at Statistics Canada applies moving averages and does not remove seasonal patterns. This procedure is intended for monthly series with at least 13 data points that do not exhibit seasonal patterns (either because no seasonality exists, or because it has been removed by seasonal adjustment).

1.0 The general formula

For each month t, the following formula is applied to estimate the trend-cycle, denoted as $T{C}_t$:

Formula 1

$$T{C}_t=\frac{{\sum }_{j=t-6}^{t+6}{I}_j{W}_j^{\left(t\right)}{Y}_j}{{\sum }_{k=t-6}^{t+6}{I}_k{W}_k^{\left(t\right)}}\text{, (1)}$$

where $Y_j$ is the value of the input series for month $j$, available for $j=1,\dots ,T$. If the value of the input series for month $j$ is available, $I_j$ is an indicator equal to 1. Otherwise, it is equal to 0. Applying this formula near the beginning or end of a series leads to undefined terms (e.g. $Y_0$ ), discussed in Section 1.1. The quantities shown as $W_j^{\left(t\right)}$ represent the moving average weights applied to month $j$ for the calculation of the trend-cycle for month t. This is referred to as the cascade linear filter, as derived by Dagum and Luati (2009) and presented in Table 1.

Applying formula (1) for each month $t=1,\dots ,T$ yields the trend-cycle series.

1.1 Applying the general formula

The weights presented in Table 1 were developed by combining several filters that are each optimal for specific purposes. The combined results provide robust trend-cycle estimates with good statistical properties. For more information, see Dagum and Luati (2009).

By design, aggregating the weights in Table 1 for all months from (t-6) to (t+6) gives an exact total of 1. This is necessary so that the level of the trend-cycle series is the same on average as the level of the input series. Note that when we derive the trend-cycle estimates for the first six and the last six months of the input series, formula (1) includes terms that are not defined, such as Y₀. However, these terms can be assumed to be 0 since they disappear when multiplied by the corresponding indicator coefficient, I₀, which equals 0 by definition. In these cases, the denominator in formula (1) represents an adjustment to the moving average weights. Referred to as the cut-and-normalize approach, this ensures that the moving average weights used to estimate the trend-cycle for each month add up to 1. In the cut-and-normalize approach, the weights of the months for which data are unavailable are redistributed proportionally to the months for which data are available. For all other months, the denominator in formula (1) is equal to 1, and the formula is reduced to a simple symmetric moving average with the weights specified in Table 1.

1.2 Alternate expression

In formula (1), a cut-and-normalize approach is used to derive the moving average weights for the first and last six months of the input series. In effect, the cut-and-normalize approach to estimating the trend-cycle employs modified moving average weights to calculate the trend-cycle of the first six months of the series and the final six months. For example, when the trend-cycle estimate for the final month of a series is calculated, the values of the six subsequent months are not yet known. The cut-and-normalize approach proportionally rescales the weights for the months that are available so that their sum is 1. An equivalent expression to formula (1) is given in formula (2), which is based on the rescaled moving average weights, ${\tilde{W}}_j^{\left(t\right)}$, given in formula (3).

Formula 2

$$T{C}_t={\sum }_{j=t-6}^{t+6}{I}_j{\tilde{W}}_j^{\left(t\right)}{Y}_j\text{, (2)}$$

Formula 3

$$\text{where}{\tilde{W}}_j^{\left(t\right)}=\frac{W_j^{\left(t\right)}}{{\sum }_{k=t-6}^{t+6}{I}_k{W}_k^{\left(t\right)}}\text{. (3)}$$

2.0 Illustration

To illustrate how to compute and apply the moving average weights, we consider a monthly series, $Y_t$, that spans from January 2010 to July 2015—a total of 67 months. The rescaled moving average weights in the formulas below have been rounded to six decimal places. This rounding will sometimes lead to an overestimation or an underestimation at the beginning and end of the series. Because of rounding errors, the trend-cycle obtained using these rounded weights will not be precise within these sections. The full-precision weights must be used to reproduce published trend-cycle estimates exactly.

Three examples below illustrate trend-cycle estimates near the beginning, middle and end of the series. These demonstrate the application of the moving averages when not all months of the 13-term moving average are available (examples 1 and 3), as well as when they are (example 2).

Example 1

For the March 2010 trend-cycle estimate (t=3 of the series), the $Y_j$ values are available only for j=1,...,9, which correspond to January 2010 to September 2010. Therefore, a nine-term moving average is used.

According to formula (3), the rescaled weight applied to January 2010 for this moving average is

$${\tilde{W}}_1^{\left(3\right)}=\frac{0.136}{\left(0.136+0.188+0.224+0.188+0.136+0.067+0.031-0.007-0.027\right)}\approx 0.145299\text{.}$$.

Approximate values of the rescaled moving average weights, ${\tilde{W}}_j^{\left(3\right)}$, calculated for the months included in the moving average to estimate the trend-cycle for month 3, are shown in Table 2.

Finally, applying formula (2) to the input series $Y_j$ gives the following expression for $T{C}_3$, the trend-cycle estimate for March 2010:

$$\begin{array}{c}T{C}_3=Y_1\text{*}\left(0.145299\right)+Y_2\text{*}\left(0.200855\right)+Y_3\text{*}\left(0.239316\right)+Y_4\text{*}\left(0.200855\right)+Y_5\\ \text{*}\left(0.145299\right)+Y_6\text{*}\left(0.071581\right)+Y_7\text{*}\left(0.033120\right)+Y_8\text{*}\left(-0.007479\right)\\ +Y_9\text{*}\left(-0.028846\right)\text{.}\end{array}$$

Example 2

For the August 2012 trend-cycle estimate (t=32 of the series), the values of $Y_j$ are available for each month from j=26,...,38, which correspond to February 2012 to February 2013. Therefore, a complete 13-term moving average is used. Because the denominator of formula (3) is exactly equal to 1 in this case, the rescaling has no effect and the weights used in the moving average are identical to the weights in Table 1.

The rescaled weight applied to August 2012 in this moving average is given by

$${\tilde{W}}_{32}^{\left(32\right)}=\frac{0.224}{\left(-0.027-0.007+0.031+0.067+0.136+0.188+0.224+0.188+0.136+0.067+0.031-0.007-0.027\right)}=0.224\text{.}$$

The rescaled moving average weights, ${\tilde{W}}_j^{\left(32\right)}$, calculated for the months included in the moving average used to calculate the trend-cycle estimate for month 32, are presented in Table 3.

Applying formula (2) to the input series $Y_j$ produces the following expression for the August 2012 trend-cycle estimate, $T{C}_{32}$:

$$\begin{array}{c}T{C}_{32}=Y_{26}\text{*}\left(-0.027\right)+Y_{27}\text{*}\left(-0.007\right)+Y_{28}\text{*}\left(0.031\right)+Y_{29}\text{*}\left(0.067\right)+Y_{30}\text{*}\left(0.136\right)+Y_{31}\\ \text{*}\left(0.188\right)+Y_{32}\text{*}\left(0.224\right)+Y_{33}\text{*}\left(0.188\right)+Y_{34}\text{*}\left(0.136\right)+Y_{35}\text{*}\left(0.067\right)+Y_{36}\\ \text{*}\left(0.031\right)+Y_{37}\text{*}\left(-0.007\right)+Y_{38}\text{*}\left(-0.027\right)\text{.}\end{array}$$

Example 3

For the July 2015 trend-cycle estimate (t=67 of the series), the values of $Y_j$ are known only for each month from j=61,...,67, which correspond to January 2015 to July 2015. Therefore, a seven-term moving average is used.

The rescaled weight applied to July 2015 in this moving average is

$${\tilde{W}}_{67}^{\left(67\right)}=\frac{0.224}{\left(0.224+0.188+0.136+0.067+0.031-0.007-0.027\right)}\approx 0.366013\text{.}$$

The rescaled moving average weights, $W_j^{\left(67\right)}$, calculated for the other months included in the moving average used to calculate the trend-cycle estimate for month 67, are presented in Table 4.

Applying formula (2) to the input series $Y_j$ gives the following expression for the July 2015 trend-cycle estimate, $T{C}_{67}$:

$$\begin{array}{c}T{C}_{67}= Y_{61}\text{*}\left(-0.044118\right)+Y_{62}\text{*}\left(-0.011438\right)+Y_{63}\text{*}\left(0.050654\right)+Y_{64}\text{*}\left(0.109477\right)\\ +Y_{65}\text{*}\left(0.222222\right)+Y_{66}\text{*}\left(0.307190\right)+Y_{67}\text{*}\left(0.366013\right)\text{.}\end{array}$$

3.0 Exact weights

A summary of the rescaled moving average weights, ${\tilde{W}}_j^{\left(t\right)}$, that are used in calculating the trend-cycle estimates over the entire series are given in Table 5.

References

Dagum, E.B., and Luati, A. 2009. “A cascade linear filter to reduce revisions and false turning points for real time trend-cycle estimation.” Econometric Reviews 28 (1–3): 40–59.

The record linkage application process can be divided into four phases:

• Phase 1: Feasibility of the study and calculating time and cost estimates
• Phase 2: Formal approval
• Phase 3: Record linkage and deliverables
• Phase 4: Retention of linked files, keys and identifiers