I want to capture the spatial effects of the neighboring countries with respect to health care in Malaysia.
How can i capture these effects if any and is there any command(s) in E-Views or Grtle for the purpose?
What variables should be most relevant, to be used for the study?
Dear Habib,
Please say what you clearly mean by 'spatial'? I think answering this question can guide you through finding relevant variables. Then you can decide on a qualitative or a quantitative approach to collect data and accomplish your study.
Best,
Ali
Hi dear Ali!
Thank you dear Ali.
Spatial means with respect to space, or geographical location(s). The effects of one location might have an influence on the other nearby location or not?
Habib
Hi Habib,
It is possible that "behaviors" of one country may influence the behaviors of its neighbor, but I can't think of any situations that I am aware of where this issue arises.
To test such a hypothesis, I would suggest conducting an interrupted time series analysis (ITSA), where you would track the outcome measure over time in the target country and in the neighboring countries. I further assume that there is a policy change that occurs at some point in the target country. If you compare the two (or more) countries over time, you can assess how the outcome changes in those countries over time. The hypothesis may be that you'd expect to see the outcome change in the neighboring country at a lag from the point in time that the policy change was implemented in the target country.
You can also introduce other relevant covariates in the model, but that will rely on content expertise and availability of variables for such an exercise.
I am attaching a paper that introduces a program that performs ITSA, that I wrote for Stata. Take a look at the examples and it should give you some idea of how to frame your research question.
Ariel
Article Conducting Interrupted Time-series Analysis for Single- and ...
There are many works online on this topic example
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwj0xpPg6cr-AhUydqQEHXiTBIEQFnoECAsQAQ&url=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC7918594%2F&usg=AOvVaw0xZT9-M7QTtNNLXNqUFoH8
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