bootstrap clustering at region level

Dear community,

I have a city-year level panel data, with 200 cities and 13 years. So each variable has size 2600x1. I have 40 variables. So the whole dataset has size 2600x40. I have about 70 parameters. I am trying to use bootstrap and get standard errors for estimates of a nonlinear problem. However, observations within a region may be correlated. I have never done boostrap before, but my plan is to:

1. Draw a sample j of 2600x40 data.
2. Compute all 70 estimates. This step invovle linear regression and fminsearch for a non-linear problem. Call these estimates . Store it in the jth column of matrix A.
3. Repeat steps above 500 times. So matrix A has size 70x500.
4. Compute the standard deviation of each row. This is the standard error for each parameter.

Does this procedure seem right?

I see that Matlab has two boostrap commands: bootstrp and bootci. Can I ask:

1. Which command is the correct one to use?
2. How to redraw samples at regional, instead of city level?
3. Can I input the original data as 40 columns, or do I have to input it as one 2600x40 matrix? The document says data could be entered as d or d1, ..., dN, but want to check if I understand it correctly...

Thank you very much for your help!!