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Phil Nguyen
Phil Nguyen
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In some international studies, authors usually use the industry-level in North America (US and Canada) to control for all-even non-North American-countries. I am quite confused about how to do that in the data set up.

For example, Dasgupta,2019 documented that

While our data limitations do not allow us to control for individual market-to-book ratios for international firms going back to 1990s, we control for industry market-to-book ratio to capture industry growth opportunities. We calculate the latter based on Compustat North America data as the three-digit SIC industry median, and we control for it for all—even non- North American—countries

From my understanding, I will merge the data regarding market-to-book ratio (MTB) of Canada and US together year by year for each industry. Afterward, I will sort the data to get the median of each industry of each year of this merged dataset. In the end, I will apply this data for all non-North America-countries by associated industries and years.

For example, in the year 1997, in the US, in the manufacturing industry, we have 4 companies with MTB equals 3,5,6,12, in. In Canada, we have 5 companies with MTB are 1,2,13,15,16 in the same year in the same industry. So, the median of MTB in manufacturing in North America in 1997 is median of {1,2,3,5,6,12,15,16}, which equals to 5.5.

So, does it mean that, every firm in manufacturing industry in every country all over the world will have the MTB=5.5 in the year 1997 in a panel dataset?

Apart from that, other than the international data limitation reason or the rich in the North America data, is there any other reason that researchers use the industry variables based on North America data?

In some international studies, authors usually use the industry-level in North America (US and Canada) to control for all-even non-North American-countries. I am quite confused about how to do that in the data set up.

For example, Dasgupta,2019 documented that

While our data limitations do not allow us to control for individual market-to-book ratios for international firms going back to 1990s, we control for industry market-to-book ratio to capture industry growth opportunities. We calculate the latter based on Compustat North America data as the three-digit SIC industry median, and we control for it for all—even non- North American—countries

From my understanding, I will merge the data regarding market-to-book ratio (MTB) of Canada and US together year by year for each industry. Afterward, I will sort the data to get the median of each industry of each year of this merged dataset. In the end, I will apply this data for all non-North America-countries by associated industries and years.

For example, in the year 1997, in the US, in the manufacturing industry, we have 4 companies with MTB equals 3,5,6,12, in Canada, we have 5 companies with MTB are 1,2,13,15,16 in the same year in the same industry. So, the median of MTB in manufacturing in North America in 1997 is median of {1,2,3,5,6,12,15,16}, which equals to 5.5.

So, does it mean that, every firm in manufacturing industry in every country all over the world will have the MTB=5.5 in the year 1997 in a panel dataset?

Apart from that, other than the international data limitation reason or the rich in the North America data, is there any other reason that researchers use the industry variables based on North America data?

In some international studies, authors usually use the industry-level in North America (US and Canada) to control for all-even non-North American-countries. I am quite confused about how to do that in the data set up.

For example, Dasgupta,2019 documented that

While our data limitations do not allow us to control for individual market-to-book ratios for international firms going back to 1990s, we control for industry market-to-book ratio to capture industry growth opportunities. We calculate the latter based on Compustat North America data as the three-digit SIC industry median, and we control for it for all—even non- North American—countries

From my understanding, I will merge the data regarding market-to-book ratio (MTB) of Canada and US together year by year for each industry. Afterward, I will sort the data to get the median of each industry of each year of this merged dataset. In the end, I will apply this data for all non-North America-countries by associated industries and years.

For example, in the year 1997, in the US, in the manufacturing industry, we have 4 companies with MTB equals 3,5,6,12. In Canada, we have 5 companies with MTB are 1,2,13,15,16 in the same year in the same industry. So, the median of MTB in manufacturing in North America in 1997 is median of {1,2,3,5,6,12,15,16}, which equals to 5.5.

So, does it mean that, every firm in manufacturing industry in every country all over the world will have the MTB=5.5 in the year 1997 in a panel dataset?

Apart from that, other than the international data limitation reason or the rich in the North America data, is there any other reason that researchers use the industry variables based on North America data?

Source Link
Phil Nguyen
Phil Nguyen
  • 307
  • 1
  • 2
  • 9

How to set up the industry-level variables in an international study based on North America data?

In some international studies, authors usually use the industry-level in North America (US and Canada) to control for all-even non-North American-countries. I am quite confused about how to do that in the data set up.

For example, Dasgupta,2019 documented that

While our data limitations do not allow us to control for individual market-to-book ratios for international firms going back to 1990s, we control for industry market-to-book ratio to capture industry growth opportunities. We calculate the latter based on Compustat North America data as the three-digit SIC industry median, and we control for it for all—even non- North American—countries

From my understanding, I will merge the data regarding market-to-book ratio (MTB) of Canada and US together year by year for each industry. Afterward, I will sort the data to get the median of each industry of each year of this merged dataset. In the end, I will apply this data for all non-North America-countries by associated industries and years.

For example, in the year 1997, in the US, in the manufacturing industry, we have 4 companies with MTB equals 3,5,6,12, in Canada, we have 5 companies with MTB are 1,2,13,15,16 in the same year in the same industry. So, the median of MTB in manufacturing in North America in 1997 is median of {1,2,3,5,6,12,15,16}, which equals to 5.5.

So, does it mean that, every firm in manufacturing industry in every country all over the world will have the MTB=5.5 in the year 1997 in a panel dataset?

Apart from that, other than the international data limitation reason or the rich in the North America data, is there any other reason that researchers use the industry variables based on North America data?