Cannot estimate difference-in-differences RE model (system is exactly singular error)

Question

I'm trying to estimate a DiD model using panel data methods (pooling, FE and RE). The model is used to determine whether a cartel presence (dummy variable E1 in regression - 1 for the cartel period and 0 otherwise) affects the consumer price of fish on the examined market (dummy variable Cartel - 1 for the supposedly cartelised market and 0 otherwise, there are two markets in total. In a DiD regression, as I understand it, I need to have an equation with E1, Cartel and their interaction term E1*Cartel (as well as some control variables - FPI (fish price index) and quarter dummy variables Q2, Q3 and Q4).

This structure can be used to estimate a linear model just fine, but when I try to actually implement panel data methods, RE in particular, R gives me the system is exactly singular error. If I understand it correctly, this means that two of the dummy variables are exactly collinear. I tested this theory and came to the conclusion that the problem is caused by the dummy variable Cartel - when I add it to the model it stops working. I don't get why though - if this variable was actually collinear with another one, shouldn't the regular lm regression have failed as well?

Any advice is greatly appreciated.

This works well:

m_E1 <- lm(Price_Index ~ E1 + Cartel + E1*Cartel + FPI + Q2 + Q3 + Q4,
           data = fish_regr)

So do these models:

m.pooled <- plm(Price_Index ~ E1 + Cartel + E1*Cartel + FPI + Q2 + Q3 + Q4, 
                data = pdata, model = "pooling")

m.fixed <- plm(Price_Index ~ E1 + Cartel + E1*Cartel + FPI + Q2 + Q3 + Q4, 
               data = pdata, model = "within")

But this gives me the error:

m.random <- plm(Price_Index ~ E1 + Cartel + E1*Cartel + Q2 + Q3 + Q4, 
                data = pdata, model = "random")

Here is the panel data (converted with index = c("Market", "Month)):

structure(list(Market = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("RU", "UK"), class = "factor"), Month = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L ), .Label = c("2009-01-31", "2009-02-28", "2009-03-31", "2009-04-30", "2009-05-31", "2009-06-30", "2009-07-31", "2009-08-31", "2009-09-30", "2009-10-31", "2009-11-30", "2009-12-31", "2010-01-31", "2010-02-28", "2010-03-31", "2010-04-30", "2010-05-31", "2010-06-30", "2010-07-31", "2010-08-31", "2010-09-30", "2010-10-31", "2010-11-30", "2010-12-31", "2011-01-31", "2011-02-28", "2011-03-31", "2011-04-30", "2011-05-31", "2011-06-30", "2011-07-31", "2011-08-31", "2011-09-30", "2011-10-31", "2011-11-30", "2011-12-31", "2012-01-31", "2012-02-29", "2012-03-31", "2012-04-30", "2012-05-31", "2012-06-30", "2012-07-31", "2012-08-31", "2012-09-30", "2012-10-31", "2012-11-30", "2012-12-31", "2013-01-31", "2013-02-28", "2013-03-31", "2013-04-30", "2013-05-31", "2013-06-30", "2013-07-31", "2013-08-31", "2013-09-30", "2013-10-31", "2013-11-30", "2013-12-31", "2014-01-31", "2014-02-28", "2014-03-31", "2014-04-30", "2014-05-31", "2014-06-30", "2014-07-31", "2014-08-31", "2014-09-30", "2014-10-31", "2014-11-30", "2014-12-31"), class = "factor"), Salmonoid = c(218.79, 225.98, 233.85, 239.88, 247.61, 256.19, 263.39, 265.7, 264.38, 261.32, 258.49, 257.18, 259.18, 262.27, 265.11, 266.43, 266.28, 266.95, 269.15, 270.19, 275.43, 280.21, 285.3, 292.06, 298.89, 301.78, 304.49, 307.23, 310.13, 310.77, 312.51, 311.66, 309.92, 308.76, 309.72, 310.08, 306.73, 307.17, 306.03, 305.09, 301.73, 299.08, 299.24, 300.39, 300.09, 299.19, 298.49, 299.38, 298.94, 299.72, 303.33, 305.38, 307.82, 309.52, 312.41, 318.07, 323.53, 326.11, 328.75, 332.44, 341.6, 347.65, 355.87, 363.61, 369.4, 372.36, 377.08, 386.36, 403.76, 418.74, 426, 445.29, 10.07, 11.69, 10.96, 11.77, 11.75, 11.28, 11.43, 11.4, 11.45, 11.53, 11.52, 11.45, 11.71, 12.74, 12.68, 13.04, 13.11, 13.72, 14.69, 14.6, 14.42, 15.29, 15.64, 15.83, 15.78, 15.66, 15.64, 14.47, 15.67, 15.55, 15.3, 14.9, 15.14, 15.75, 15.36, 14.5, 14.96, 16.39, 16.05, 15.87, 16.22, 15.69, 15.7, 16.13, 15.66, 15.96, 15.23, 16.19, 16.15, 14.52, 14.95, 14.53, 15.36, 15.7, 15.46, 15.49, 15.39, 16.44, 16.39, 16.34, 16.16, 17.09, 17.27, 16.41, 17.44, 17.14, 17.89, 17.29, 16.79, 17.11, 17.16, 16.75), E1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L ), E2 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), E4 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), E3 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), Cartel = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), Q2 = c(0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L), Q3 = c(0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L), Q4 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L), FPI = c(3, 3.2, 3.4, 3.7, 4.2, 4.1, 4.2, 3.4, 3.4, 3.1, 3.3, 3.4, 3.5, 4.2, 4.6, 5, 5.2, 4.9, 5, 5.1, 4.6, 4.5, 4.3, 5, 5, 5.2, 5.2, 5.5, 5, 4.1, 3.7, 3.4, 3.1, 2.7, 3, 3.3, 3.2, 3.5, 3.7, 3.7, 3.8, 3.4, 3.4, 3.6, 3.4, 3.3, 3.5, 4.1, 4.6, 4.9, 5, 5.5, 5.6, 5.3, 5.6, 5.2, 4, 4.5, 4.7, 5.9, 5.8, 5.7, 5.3, 5.5, 4.8, 4.3, 4.7, 4, 4, 4.1, 4.7, 5, 3, 3.2, 3.4, 3.7, 4.2, 4.1, 4.2, 3.4, 3.4, 3.1, 3.3, 3.4, 3.5, 4.2, 4.6, 5, 5.2, 4.9, 5, 5.1, 4.6, 4.5, 4.3, 5, 5, 5.2, 5.2, 5.5, 5, 4.1, 3.7, 3.4, 3.1, 2.7, 3, 3.3, 3.2, 3.5, 3.7, 3.7, 3.8, 3.4, 3.4, 3.6, 3.4, 3.3, 3.5, 4.1, 4.6, 4.9, 5, 5.5, 5.6, 5.3, 5.6, 5.2, 4, 4.5, 4.7, 5.9, 5.8, 5.7, 5.3, 5.5, 4.8, 4.3, 4.7, 4, 4, 4.1, 4.7, 5), Price_Index = c(0.713298341, 0.736739152, 0.762396896, 0.78205588, 0.807257197, 0.835229681, 0.858703094, 0.866234147, 0.861930688, 0.851954488, 0.842728132, 0.838457275, 0.844977668, 0.855051674, 0.864310632, 0.868614091, 0.868125061, 0.870309393, 0.877481824, 0.880872429, 0.897955857, 0.913539595, 0.930133994, 0.952172921, 0.974440061, 0.983862028, 0.99269716, 1.001630098, 1.011084667, 1.013171193, 1.018843934, 1.016072768, 1.010400026, 1.006618198, 1.009747987, 1.010921657, 1, 1.001434486, 0.997717863, 0.994653278, 0.983699019, 0.975059499, 0.97558113, 0.979330356, 0.978352297, 0.97541812, 0.973135983, 0.976037557, 0.974603071, 0.977146024, 0.988915333, 0.995598735, 1.003553614, 1.009095948, 1.018517915, 1.036970626, 1.054771297, 1.063182604, 1.071789522, 1.083819646, 1.113683044, 1.133407231, 1.160206044, 1.185439963, 1.2043165, 1.213966681, 1.229354807, 1.259609428, 1.316336843, 1.365174584, 1.388843608, 1.451732794, 0.694482759, 0.806206897, 0.755862069, 0.811724138, 0.810344828, 0.777931034, 0.788275862, 0.786206897, 0.789655172, 0.795172414, 0.794482759, 0.789655172, 0.807586207, 0.87862069, 0.874482759, 0.899310345, 0.904137931, 0.946206897, 1.013103448, 1.006896552, 0.994482759, 1.054482759, 1.07862069, 1.091724138, 1.088275862, 1.08, 1.07862069, 0.997931034, 1.080689655, 1.072413793, 1.055172414, 1.027586207, 1.044137931, 1.086206897, 1.059310345, 1, 1.031724138, 1.130344828, 1.106896552, 1.094482759, 1.11862069, 1.082068966, 1.082758621, 1.112413793, 1.08, 1.100689655, 1.050344828, 1.116551724, 1.113793103, 1.00137931, 1.031034483, 1.002068966, 1.059310345, 1.082758621, 1.066206897, 1.068275862, 1.06137931, 1.133793103, 1.130344828, 1.126896552, 1.114482759, 1.17862069, 1.191034483, 1.131724138, 1.202758621, 1.182068966, 1.233793103, 1.192413793, 1.157931034, 1.18, 1.183448276, 1.155172414)), .Names = c("Market", "Month", "Salmonoid", "E1", "E2", "E4", "E3", "Cartel", "Q2", "Q3", "Q4", "FPI", "Price_Index" ), row.names = c("RU-2009-01-31", "RU-2009-02-28", "RU-2009-03-31", "RU-2009-04-30", "RU-2009-05-31", "RU-2009-06-30", "RU-2009-07-31", "RU-2009-08-31", "RU-2009-09-30", "RU-2009-10-31", "RU-2009-11-30", "RU-2009-12-31", "RU-2010-01-31", "RU-2010-02-28", "RU-2010-03-31", "RU-2010-04-30", "RU-2010-05-31", "RU-2010-06-30", "RU-2010-07-31", "RU-2010-08-31", "RU-2010-09-30", "RU-2010-10-31", "RU-2010-11-30", "RU-2010-12-31", "RU-2011-01-31", "RU-2011-02-28", "RU-2011-03-31", "RU-2011-04-30", "RU-2011-05-31", "RU-2011-06-30", "RU-2011-07-31", "RU-2011-08-31", "RU-2011-09-30", "RU-2011-10-31", "RU-2011-11-30", "RU-2011-12-31", "RU-2012-01-31", "RU-2012-02-29", "RU-2012-03-31", "RU-2012-04-30", "RU-2012-05-31", "RU-2012-06-30", "RU-2012-07-31", "RU-2012-08-31", "RU-2012-09-30", "RU-2012-10-31", "RU-2012-11-30", "RU-2012-12-31", "RU-2013-01-31", "RU-2013-02-28", "RU-2013-03-31", "RU-2013-04-30", "RU-2013-05-31", "RU-2013-06-30", "RU-2013-07-31", "RU-2013-08-31", "RU-2013-09-30", "RU-2013-10-31", "RU-2013-11-30", "RU-2013-12-31", "RU-2014-01-31", "RU-2014-02-28", "RU-2014-03-31", "RU-2014-04-30", "RU-2014-05-31", "RU-2014-06-30", "RU-2014-07-31", "RU-2014-08-31", "RU-2014-09-30", "RU-2014-10-31", "RU-2014-11-30", "RU-2014-12-31", "UK-2009-01-31", "UK-2009-02-28", "UK-2009-03-31", "UK-2009-04-30", "UK-2009-05-31", "UK-2009-06-30", "UK-2009-07-31", "UK-2009-08-31", "UK-2009-09-30", "UK-2009-10-31", "UK-2009-11-30", "UK-2009-12-31", "UK-2010-01-31", "UK-2010-02-28", "UK-2010-03-31", "UK-2010-04-30", "UK-2010-05-31", "UK-2010-06-30", "UK-2010-07-31", "UK-2010-08-31", "UK-2010-09-30", "UK-2010-10-31", "UK-2010-11-30", "UK-2010-12-31", "UK-2011-01-31", "UK-2011-02-28", "UK-2011-03-31", "UK-2011-04-30", "UK-2011-05-31", "UK-2011-06-30", "UK-2011-07-31", "UK-2011-08-31", "UK-2011-09-30", "UK-2011-10-31", "UK-2011-11-30", "UK-2011-12-31", "UK-2012-01-31", "UK-2012-02-29", "UK-2012-03-31", "UK-2012-04-30", "UK-2012-05-31", "UK-2012-06-30", "UK-2012-07-31", "UK-2012-08-31", "UK-2012-09-30", "UK-2012-10-31", "UK-2012-11-30", "UK-2012-12-31", "UK-2013-01-31", "UK-2013-02-28", "UK-2013-03-31", "UK-2013-04-30", "UK-2013-05-31", "UK-2013-06-30", "UK-2013-07-31", "UK-2013-08-31", "UK-2013-09-30", "UK-2013-10-31", "UK-2013-11-30", "UK-2013-12-31", "UK-2014-01-31", "UK-2014-02-28", "UK-2014-03-31", "UK-2014-04-30", "UK-2014-05-31", "UK-2014-06-30", "UK-2014-07-31", "UK-2014-08-31", "UK-2014-09-30", "UK-2014-10-31", "UK-2014-11-30", "UK-2014-12-31"), class = c("pdata.frame", "data.frame"), index = structure(list( Market = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L ), .Label = c("RU", "UK"), class = "factor"), Month = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L), .Label = c("2009-01-31", "2009-02-28", "2009-03-31", "2009-04-30", "2009-05-31", "2009-06-30", "2009-07-31", "2009-08-31", "2009-09-30", "2009-10-31", "2009-11-30", "2009-12-31", "2010-01-31", "2010-02-28", "2010-03-31", "2010-04-30", "2010-05-31", "2010-06-30", "2010-07-31", "2010-08-31", "2010-09-30", "2010-10-31", "2010-11-30", "2010-12-31", "2011-01-31", "2011-02-28", "2011-03-31", "2011-04-30", "2011-05-31", "2011-06-30", "2011-07-31", "2011-08-31", "2011-09-30", "2011-10-31", "2011-11-30", "2011-12-31", "2012-01-31", "2012-02-29", "2012-03-31", "2012-04-30", "2012-05-31", "2012-06-30", "2012-07-31", "2012-08-31", "2012-09-30", "2012-10-31", "2012-11-30", "2012-12-31", "2013-01-31", "2013-02-28", "2013-03-31", "2013-04-30", "2013-05-31", "2013-06-30", "2013-07-31", "2013-08-31", "2013-09-30", "2013-10-31", "2013-11-30", "2013-12-31", "2014-01-31", "2014-02-28", "2014-03-31", "2014-04-30", "2014-05-31", "2014-06-30", "2014-07-31", "2014-08-31", "2014-09-30", "2014-10-31", "2014-11-30", "2014-12-31"), class = "factor")), .Names = c("Market", "Month" ), class = c("pindex", "data.frame"), row.names = c(NA, 144L)))

Hard to tell without data, perhaps you need to specify id and time variables using option `index=` within `plm()`, consider `?plm` for that. Better provide your example data with `dput(pdata)` or `dput(pdata[sample(nrow(pdata), 10), ])` rather than an image to make your issue reproducible. Anyway for RE you could consider `lmer()` of the `lme4` package. — jay.sf, Jun 05 '18 at 12:22
@jaySf I think I figured out the problem - when I convert the data to panel data, it switches values around and sorts them by months: Jan of 2009-2014, Feb of 2009-2014 etc., when it's actually supposed to be regular monthly data: Jan-Dec 2009, Jan-Dec 2010, etc. Because of this the dummy variables get mixed up. Is there a way to remedy this? Thanks for the quick response btw. — DenizKutlu, Jun 05 '18 at 18:34
Hm, you may want to consider the [`lubridate` package](https://cran.r-project.org/web/packages/lubridate/vignettes/lubridate.html) — jay.sf, Jun 05 '18 at 18:43
@jaySf I did manage to sort the observations properly, but the main problem somehow still persists. — DenizKutlu, Jun 05 '18 at 21:02

Cannot estimate difference-in-differences RE model (system is exactly singular error)

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