I have two data sets one is cross sectional census data with 10 years interval and another one is time series data (monthly) for several years. Now I want to perform statistical time series analysis on this both dataset in a single model. Is it possible?
It really depends on the outcome you want from your analysis.
The most straightforward approaches might be resampling:
Interpolate the 10-year census data to month granularity. The interpolation might be linear, polynomial, etc. This effectively imposes a strong assumption in the dynamics of the data. This may make sense for some variables but not for others. And you are probably introducing a lot of variance in the obtained conclusions.
Aggregate the monthly time series into 10-year granularity. This may not be very useful if you want to predict something with an horizon less than 10 years...