<p>In your situation (after reading the comments) I would use the 10 year data over the 2 year company specific data, unless you can identify some reason why your specific company is especially atypical for the industry.</p>

<p>Considering the length of business cycles we typically see in the developed world, about 5 years, any 2 year period may not be reflective of the future, near or distant. The effects of independent variables like interest rate and inflation rate will not be accurately calculated because there is a strong possibility they will be very similar over a 2 year period (such as in the last two years in the United States), and therefore the data will not be sufficient to measure the difference these factors make.</p>

<p>Longer periods of time will solve this problem. There is no number of data that someone can point out and say "10 years is not sufficient but 10 years and 1 month is". In other words there is no cutoff, but longer periods of time, or in general larger sample sizes, are better and in this case outweigh the benefits of more specific data (although this should be decided on a case by case basis).</p>

CC BY-SA 3.0
2015-05-28T14:06:35.443Z
2015-05-29T01:37:14.430Z
2015-05-29T01:37:14.430Z
Tyler Wyckoff
<p>I want to forecast demand for the cement industry. I have data for 10 years- Monthly data. Is that desirable for forecasting?</p>

CC BY-SA 3.0
2015-05-28T06:14:37.453Z
Hard to say without more information in your question. That much time series data seems like it would be sufficient in general. Be careful with the conclusions you try and draw from your analysis though.
Jamzy
CC BY-SA 3.0
2015-05-28T09:11:20.543Z
Initially the company provided me with their monthly sales and price data of two years but not sure of how accurate the forecast will be, I thought of doing it for the entire cement industry as the data I am getting from various sources is for 10-20 years.
Cha
CC BY-SA 3.0
2015-05-28T09:11:28.920Z
The dependent variable being production of cement The independent variables selected are Production of( Coal, steel, electricity, Oil),GDP, Inflation rate, Interest rate, Import export. My question is: Should I go for the two year data which the country has provided me with or should I take the data for the entire industry. ( I can change my aim from specific to general). Thanks!
Cha
<time-series>
Is 10 years monthly data enough for forecasting?
Cha
# Is 10 years monthly data enough for forecasting?

(Asked by: username_0 on 2015-05-28)

I want to forecast demand for the cement industry. I have data for 10 years- Monthly data. Is that desirable for forecasting?

**Tags:** time-series

> **Comments:**
> **username_1**: Hard to say without more information in your question. That much time series data seems like it would be sufficient in general. Be careful with the conclusions you try and draw from your analysis though.  
> **username_0**: Initially the company provided me with their monthly sales and price data of two years but not sure of how accurate the forecast will be, I thought of doing it for the entire cement industry as the data I am getting from various sources is for 10-20 years.  
> **username_0**: The dependent variable being production of cement The independent variables selected are Production of( Coal, steel, electricity, Oil),GDP, Inflation rate, Interest rate, Import export. My question is: Should I go for the two year data which the country has provided me with or should I take the data for the entire industry. ( I can change my aim from specific to general). Thanks!  

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## 1 answers

### Answer by username_2 on 2015-05-28. Score: 3

In your situation (after reading the comments) I would use the 10 year data over the 2 year company specific data, unless you can identify some reason why your specific company is especially atypical for the industry.

Considering the length of business cycles we typically see in the developed world, about 5 years, any 2 year period may not be reflective of the future, near or distant. The effects of independent variables like interest rate and inflation rate will not be accurately calculated because there is a strong possibility they will be very similar over a 2 year period (such as in the last two years in the United States), and therefore the data will not be sufficient to measure the difference these factors make.

Longer periods of time will solve this problem. There is no number of data that someone can point out and say "10 years is not sufficient but 10 years and 1 month is". In other words there is no cutoff, but longer periods of time, or in general larger sample sizes, are better and in this case outweigh the benefits of more specific data (although this should be decided on a case by case basis).


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