I am trying to estimate a non-linear model like the example in the DYNARE user guide. But I am confused on what kind of data to use.
Am I to estimate using the data as they are, for example, GDP in its actual form, because my model is non-linear?
I will be glad if anyone can help clarify this.
Thanks in advance
What exactly do you mean by this?
Thank you for replying. This is an example of one of the equations in my model
yF = a k^alpha hF^(1-alpha);
the equation is a non-linear model of output
To estimate, my model using bayesian technique, I am to provide my dataset.
My question is that should my output data (gdp) be in its raw from as gathered from World Bank or I am to do a form of transformation.
I hope this is clearer now. Thanks
Maybe I will try to be more clear about what is unclear from my perspective:
You have used the term “actual form” and also “raw from” when referencing the data you are collecting for use in estimation. I do not know what you mean by these two distinct ways of characterizing the data. Perhaps you could be more specific about the type of data you have collected and what the different “forms” you are trying to decide between. At the moment there is no way to know if you mean “level vs growth rate” or “level vs per capita” or “filtered vs unfiltered” or any number of other ways we can think about macro data.
Your model is a suggestion for the data generating process. Most DSGE models are inherently nonlinear, but unless there are particular nonlinearities characteristics you are hoping to explore (e.g. the role of risk or stochastic volatility) what you probably want to do is “estimate a first order approximation of the model” which will itself be given as a typical linear state-space model. This is what e.g. Smets and Wouters (2007) do. The phrase “estimate a nonlinear model” can be taken to mean a variety of things, so it would be useful for you to explain your goal in more detail.
Thank you for your response.
- what I meant regarding actual form is whether I to estimate using data at levels.
I have attached my model to give you a better understanding.
I am still new with DSGE so a lot of things are still unclear for me.
Trial.mod (4.0 KB)
Don’t be intimidated by DSGE models: at their core they are just a tool for modeling fluctuations in key macroeconomic statistics. It isn’t always apparent in the beginning, but the underlying intuition is more-or-less the same as the non-microfounded models you probably have studied in undergraduate classes e.g. the IS-LM-PC or IS-LM-AS-AD models.
That’s all to say that the answer to the question “Which data should I use?” is not well defined, because it depends on the model you are studying and your specific research question. You should try to explain these. If you can’t, then you probably aren’t ready to begin worrying about gathering data for estimation in the first place. If you can, then myself and the others on this forum will be better able to help you.