Hi everyone,

I'm trying to model the choices among different products from 2000 to 2018 in different areas. I have two ideas of modelling but not sure which one is better and is more achievable in STATA.

The first idea is to model the market share of different brands using panel data with regional variables. The dataset looks like the following.
`````````````````````````````````````````````````` `````````````````````````````````````````````````` `````````````````````````````````````````````````` ````````````````````````
ln(MarketShareOfTheProduct) Product Area AveragePriceOfTheProduct AttributesOfTheProduct Year
xxxx(numeric) A Spain(string) xxxxxx(numeric) sweet(string) 2000(numeric)
xxxx(numeric) A Italy(string) xxxxxx(numeric) sweet(string) 2001(numeric)
xxxx(numeric) A Greece(string) xxxxxx(numeric) sweet(string) 2002(numeric)
xxxx(numeric) A UK(string) xxxxxx(numeric) sweet(string) 2003(numeric)
xxxx(numeric) A Spain(string) xxxxxx(numeric) spicy(string) 2000(numeric)
xxxx(numeric) A Italy(string) xxxxxx(numeric) spicy(string) 2001(numeric)
xxxx(numeric) A Greece(string) xxxxxx(numeric) spicy(string) 2002(numeric)
xxxx(numeric) A UK(string) xxxxxx(numeric) spicy(string) 2003(numeric)
xxxx(numeric) B Spain(string) xxxxxx(numeric) sweet(string) 2000(numeric)
xxxx(numeric) B Italy(string) xxxxxx(numeric) sweet(string) 2001(numeric)
xxxx(numeric) B Greece(string) xxxxxx(numeric) sweet(string) 2002(numeric)
xxxx(numeric) B UK(string) xxxxxx(numeric) sweet(string) 2003(numeric)
xxxx(numeric) B Spain(string) xxxxxx(numeric) spicy(string) 2000(numeric)
xxxx(numeric) B Italy(string) xxxxxx(numeric) spicy(string) 2001(numeric)
xxxx(numeric) B Greece(string) xxxxxx(numeric) spicy(string) 2002(numeric)
xxxx(numeric) B UK(string) xxxxxx(numeric) spicy(string) 2003(numeric)
...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​......



The second idea is to use the multinominal logit model to capture the choice of different products. Each observation represents one purchase decision. As the following.
`````````````````````````````````````````````````` `````````````````````````````````````````````````` `````````````````````````````````````````````````` ````````````````````````
Product Area AveragePriceOfTheProduct AttributesOfTheProduct Year
A Greece(string) xxxxxx(numeric) sour(string) 2000(numeric)
C Italy(string) xxxxxx(numeric) sweet(string) 2000(numeric)
B Greece(string) xxxxxx(numeric) sweet(string) 2002(numeric)
C Italy(string) xxxxxx(numeric) sour(string) 2000(numeric)
B Spain(string) xxxxxx(numeric) spicy(string) 2003(numeric)
C Italy(string) xxxxxx(numeric) spicy(string) 2000(numeric)
A Greece(string) xxxxxx(numeric) spicy(string) 2001(numeric)
A UK(string) xxxxxx(numeric) sour(string) 2001(numeric)
B Spain(string) xxxxxx(numeric) sweet(string) 2003(numeric)
C Italy(string) xxxxxx(numeric) sour(string) 2001(numeric)
B Greece(string) xxxxxx(numeric) sweet(string) 2001(numeric)
A Greece(string) xxxxxx(numeric) sweet(string) 2003(numeric)
C Spain(string) xxxxxx(numeric) sour(string) 2000(numeric)
B Italy(string) xxxxxx(numeric) spicy(string) 2001(numeric)
​​​​​​​C Greece(string) xxxxxx(numeric) sour(string) 2002(numeric)
B UK(string) xxxxxx(numeric) spicy(string) 2001(numeric)
...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​...... ​​​​​​​......



It will be really appreciated if any suggestions can be provided regarding my question.

Many thanks!!!!