Hi,

I am doing an econometrics course where I am to do a regression analysis on some firm data.

I want to analyze some shipping data of frozen goods to predict the temperature of the shipped goods at their end destination.

My problem is that I am unsure which kind of analysis to make when I am interested in both time-variant and in-variant variables

My data:

I have approx 100 data points for different shipments. For each data point, I have the starting temperature of the products (same for all) and the end temperature after arriving at their end destination. That is my dependent variable. Additionally, I have data for 4 other independent variables:

kg of dry ice (In-variant)

kg of products shipped (In-variant)

time of shipment in days (time-variant)

Ambient temperature during shipment (In-variant)

My model is then:

The temperature of the shipped products = kg of Dry Ice + kg of Products + Time + Ambient temperature

Because of my Time variable, I believe that I should du a Panel Data analysis. But as I also want to estimate the effect of some in-variant variables I should use a Random effect approach.

Am I correct in my reasoning?

Or could i simply just frame the model as Cross-sectional not taking into account the time periods (as all shipments have the same starting temperature)

I am doing an econometrics course where I am to do a regression analysis on some firm data.

I want to analyze some shipping data of frozen goods to predict the temperature of the shipped goods at their end destination.

My problem is that I am unsure which kind of analysis to make when I am interested in both time-variant and in-variant variables

My data:

I have approx 100 data points for different shipments. For each data point, I have the starting temperature of the products (same for all) and the end temperature after arriving at their end destination. That is my dependent variable. Additionally, I have data for 4 other independent variables:

kg of dry ice (In-variant)

kg of products shipped (In-variant)

time of shipment in days (time-variant)

Ambient temperature during shipment (In-variant)

My model is then:

The temperature of the shipped products = kg of Dry Ice + kg of Products + Time + Ambient temperature

Because of my Time variable, I believe that I should du a Panel Data analysis. But as I also want to estimate the effect of some in-variant variables I should use a Random effect approach.

Am I correct in my reasoning?

Or could i simply just frame the model as Cross-sectional not taking into account the time periods (as all shipments have the same starting temperature)

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