linearmodels | Additional linear models including instrumental variable | Analytics library

Based on the work of Kuo et al (Kuo, H.-I., Chen, C.-C., Tseng, W.-C., Ju, L.-F., Huang, B.-W. (2007). Assessing impacts of SARS and Avian Flu on international tourism demand to Asia. Tourism Management. Retrieved from: https://www.sciencedirect.com/science/article/abs/pii/S0261517707002191?via%3Dihub), I am measuring the effect of COVID-19 on tourism demand.

My panel data can be found here: https://www.dropbox.com/s/t0pkwrj59zn22gg/tourism_covid_data-total.csv?dl=0

I would like to use a first-difference transformation model(GMMDIFF) and treat the lags of the dependent variable (tourism demand) as instruments for the lagged dependent variable. The dynamic and first difference version of the tourism demand model: Δyit = η2Δ yit-1 + η3 ΔSit + Δuit

where, y is tourism demand, i refers to COVID-19 infected countries, t is time, S is the number of SARS cases, and u is the fixed effects decomposition of the error term.

Up to now, using python I managed to get some results using the Panel OLS:

I keep getting an error when I install python packages in Jupyter.

Even after restarting the kernel, I still get the "& was unexpected at this time." error and cannot call functions from the package.Any idea how to resolve this?

I am building a model, using plm() package.

One of my x variables contains NAs because I used a t-1 lag calculations.

My R code looks like this

I use Python to analyze data in Jupyter Notebooks, which I convert to PDFs to share with coauthors (jupyter nbconvert --to pdf). I often use linearmodels.panel.results.compare() to compare panel regression estimates from the linearmodels package. However, the PDF conversion process converts the compare() output to a fixed-width font that is much too wide for the PDF (I will provide the code below):

Can I pretty print the output of compare() when I convert a Jupyter Notebook to PDF?

A possible solution is to convert the compare() output to a data frame. The option pd.options.display.latex.repr = True pretty prints data frames when I convert to PDF. For example:

In the notebook, the compare() output formats nicely and looks like a data frame. However, it is not a data frame, and I have failed to convert it to a data frame.

Is there an alternative solution to compare the pretty print the results of linearmodels package output?

Here is the code that generates the tables above (copy and paste into a Jupyter Notebook code cell):

How can I print out the summary table of a fitted linearmodels object as latex?

For example, how can I print res as latex code?

I have a dataframe which is a time series. I am using the function lm to build a multivariate regression model.

I have the following panel stored in df:

• y is the number of protests in each district
• constant is a column full of ones
• x1 is the proportion of the district's area covered by a mobile network provider
• x2 is the population count in each district (note that it is fixed in time)

How can I run the following model in Python?

Here's what I tried

I am relatively new to Python and Pycharm, so I don't know if it is a silly question. Suddenly I got a strange problem: the summary output from any kind of regression in python console is not correctly aligned but, if I run the script from terminal, it is perfectly aligned. Some days ago it worked well but now I have this problem with linearmodels and statsmodels. If you could help me, I'd be very happy, because it's not easy to read it.

This is an example of code that generates the problem.

I am trying to estimate a panel regression (see: https://bashtage.github.io/linearmodels/doc/panel/examples/examples.html)

My data is formatted like that (thats just an example snippet; in the orginal file there are 11 columns plus the timestamp and thousands of rows):

What I have