Synthetic control method: placebo test error: system is computationally singular

Question

I am currently doing an analysis of the effect of taxation on the institutions of a country. I am using the synthetic controls method to determine the treatment effect on Bolivia. The synth() command works fine, the placebo (with country 8 = Bhutan instead of country 9 = Bolivia) does however not. It generates the repeated error message:

Error in solve.default(AP, c(c.x, c.y)) : system is computationally singular: reciprocal condition number = 9.90619e-17

I have attached the code. You can find the dataset under the following link: totalB-Dataset

I cannot figure out why the first synth() command works while the exact same only with a different country does not. I have tried using a larger tolerance. Additionally, I have run a regression and do not detect singularity there.

I would very much appreciate any help!

creates matrices to provide inputs for synth()

  dataprep.out <-
  dataprep(foo = totalB,
       predictors = c("vdem_corr", 
                      "fh_ipolity2", 
                      "TotTax", 
                      "TotRev") ,
       predictors.op = "mean" ,
       time.predictors.prior = 1990:1998 ,
       special.predictors = list(
         list("gle_rgdpc" , 1990:1998 , "mean"),
         list("wdi_educ" ,      seq(1990,1998,2), "mean"),
         list("gle_pop",          seq(1990,1998,2), "mean"),
         list("wdi_urb" ,      seq(1990,1998,2), "mean"),
         list("wdi_popdens", 1998, "mean"),
         list("wdi_land", 1998, "mean"),
         list("conflict", 1998, "mean")
       ),
       dependent = "political_abs",
       unit.variable = "countryID",
       unit.names.variable = "country",
       time.variable = "year",
       treatment.identifier = 9,
       controls.identifier = c(1:8,10:74),
       time.optimize.ssr = 1990:1998,
       time.plot = 1990:2010

)

synth.out <- synth(data.prep.obj = dataprep.out,
               method = "BFGS")

Now Placebo-test:

dataprep.out <-
  dataprep(foo = totalB,
       predictors = c("vdem_corr", 
                      "fh_ipolity2", 
                      "TotTax", 
                      "TotRev") ,
       predictors.op = "mean" ,
       time.predictors.prior = 1990:1998 ,
       special.predictors = list(
         list("gle_rgdpc" , 1990:1998 , "mean"),
         list("wdi_educ" ,      seq(1990,1998,2), "mean"),
         list("gle_pop",          seq(1990,1998,2), "mean"),
         list("wdi_urb" ,      seq(1990,1998,2), "mean"),
         list("wdi_popdens", 1998, "mean"),
         list("wdi_land", 1998, "mean"),
         list("conflict", 1998, "mean")
       ),
       dependent = "political_abs",
       unit.variable = "countryID",
       unit.names.variable = "country",
       time.variable = "year",
       treatment.identifier = 8,
       controls.identifier = c(1:7,9:74),
       time.optimize.ssr = 1990:1998,
       time.plot = 1990:2010

)

synth.out <- synth(data.prep.obj = dataprep.out,
               method = "BFGS")