My dependent variable consists of cross-sectional data with 8 observations, while the independent variables consist of time series data with 45 observations.
If I understand you have 1 measurement of your dependent variable for each of the 8 agents, companies, schools, or similar. For each unit, you have a set of time series with 45 observations. Can you explain what you mean by a specific regression model? It is not at all obvious how you can apply time series or panel data analysis. Perhaps I do not understand.
I am interested in studying in Determinance of Poverty Alleviation in the Philippines. The possible secondary data variable is the povery incidence and poverty head count ratio collected every 3 years. The regressor are time series. What statistcal model could you recommend sir. It is required in our major to use time seriesseries regression model.
Based on the information you provided, it seems like you have a small sample size for the dependent variable (cross-sectional data) compared to the independent variables (time series data). In this case, you could consider conducting a panel data analysis or a fixed effects regression.
It's important to note that with only eight cross-sectional observations, your sample size is quite small, which can limit the statistical power and generalizability of your results. However, with panel data or fixed effects models, you can potentially leverage the time series component to gain more insights, as it provides additional variation in the data.
Cheers
A time series regression model will have the form
y_t = \beta_1 + \beta_2 x_{2t} + \beta_3 x_{3t} + \dots + \beta_k x_{kt} +u_t
where y is time-series of the dependent variable and
x_2,x_3,\dots,x_k are explanatory time series variables. (Certain conditions must be satisfied if the coefficients are to be estimated. There are additional problems to be addressed if any of the series are non-stationary)
While I have seen studies with 30 observations of each variable that have provided useful results generally considerably more observations are usually required.
Look at your data. As far as I can tell you do not have the necessary time series dependent variable to do a time series regression. Perhaps I still do not understand.
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