I am working on the economic history of Switzerland and I would like to know which determinants foster industrialization during the 19th century.
I am working with time-series. My dependent variable is the Gross added value of Swiss industries and I have 5 explanatory variables (like education, railway, tariffs etc.). The times period studied runs from 1890 to 1913.
I first used a VAR model but reviewers are not so convinced... They prefer panel data (but I don't have !) or they think that VAR is unusual...
So, do you have any idea about the macroeconometric model I should use to deal with my research question ?
Thanks a lot !!
Hi Charles, I visited Switzerland twice for 1-month and 6-month internships. Nice country. Yeah, Switzerland's industrialization should be a nice research topic, but I wonder about your period of study. Do previous studies consider 1890-1913 as a period of insustrialization in Switzerland? Do you have quarterly or monthly data for running the VAR model? For how many Swiss industries do you have the gross added value? Of course (since Einstein's job in Switzerland), do you have the time series of Swiss patents for that period? By industry or broken by type of patents? Considering the empirical section of your study, (if you only have annual data) I would strongly recomend to add the 40 or 50 years after the period of study because a plain VAR model is not good for small samples of data (a Vector Error Correction -VEC- model should work better for such data, instead). But there is another reason explaining the cold reaction of the reviewers: a VAR model is not quite useful for discovering the industrialization determinants since it is an "atheoretical" statistical model: you may need a "Structural VAR" (aka SVAR model) or better a Structural VEC (SVEC) model. Then you will be able (abstracting from the data frequency I already mentioned) to propose a theoretical structure (meaning, useful research estimated parameters) to discuss following your hypotheses. Those hypotheses should come from the previous section, the core section, which is the "theoretical" section. Such a section should consider at least the hypothesis you can select from reading many studies about economic history of Switzerland BUT also review some growth models, like the classic ones usually reviewed in macroeconomics' textbooks (Solow model, etc.) and other more recent ones like Romer's model (which consider the idea of Research & Development (please remember my idea about patents). For discovering those models, Romer's book for graduate students is the best. Finally, allow me a personal comment: I do like reading about economic history because it is a great companion for macroeconomic economists. It is such a down-to-Earth topic !
Dear Charles,
Of course it is expected that the panelists are not so convinced with your VAR model.
Since your aim is to analyse the determinants of industrialization, then a regression model is best suitable for you work. There are several macroeconometric panel data models you can adopt.
You may first need to determine whether you are working with a static or dynamic panel. However, since you are looking at determinants, I suspect you are likely to have a dynamic panel model.
Then you can consider models like dynamic panel GMM, Instrumental Variables approach, 2SLS, among others.
If you need assistance with good articles as a guide, please kindly notify me. I have few Published articles that can be of help.
Good luck
I have the feeling that you should first try a static model and then examine dynamic ones.
The fact that you are using gross value added (i.e. an output variable) automatically brings to mind a production function:
GVA = F(LABOUR, CAPITAL, TECHNOLOGY LEVEL)
You should be able to get some data on employment and capital equipment in the industries of question, at least.
Therefore, try:
ln(GVA) = a0 + a1 * t + a2 * ln(Labour) + a3 *ln(Capital) + u,
where ln = natural logs and t = a linear trend (i.e. proxy for exogenous technological change).
After this 'basic' model is determined and estimated, then you can also try adding other, additional factors that may also influence industrialization, such as the ones you already examine or the ones suggested from the colleagues, above.
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