Dear Stata Users,

I am trying to analyze the impact of minimum wages on employment (divided into formal sector employment and informal sector employment) but the equation for informal sector employment failed to converge despite giving me results.
I use the exact same independent variables for all of my equations which consist of: minimum wage, educational attainment (no. of people with a high school degree and a college degree or higher), population, GDP, and productivity.

The weight matrix I use is an inverse distance weight matrix.
The command I use is XSMLE and I am using Stata 15.1.

The results I obtain for the formal sector employment equation are as expected.
However, not so for informal sector employment.

The results I get (with informal sector employment as the dependent variable) are as follows:

Code:
. xsmle logtotinf logrealmw loglagrealmw loghs logcollege logpop loggdp logprod, wmat(W) model(sdm) fe type(both) vce(robust) effects no
> log dlag(1)
Warning: All regressors will be spatially lagged

convergence not achieved
Computing marginal effects standard errors using MC simulation...

Dynamic SDM with spatial and time fixed-effects      Number of obs =       364

Group variable: province                          Number of groups =        26
Time variable: year                                   Panel length =        14

R-sq:    within  = 0.5431
         between = 0.9600
         overall = 0.9534

Mean of fixed-effects =  1.6819

Log-pseudolikelihood =   345.4902
                              (Std. Err. adjusted for 26 clusters in province)
------------------------------------------------------------------------------
             |               Robust
   logtotinf |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Main         |
   logtotinf |
         L1. |   .2285767   .0833368     2.74   0.006     .0652395    .3919138
             |
   logrealmw |  -.1383967   .0564361    -2.45   0.014    -.2490093   -.0277841
loglagrealmw |   .0791953   .0413412     1.92   0.055     -.001832    .1602225
       loghs |  -.1067864   .0541804    -1.97   0.049     -.212978   -.0005948
  logcollege |  -.0435969   .0201391    -2.16   0.030    -.0830688    -.004125
      logpop |  -.3501759   .1223771    -2.86   0.004    -.5900305   -.1103212
      loggdp |    .989117   .0997162     9.92   0.000     .7936768    1.184557
     logprod |  -1.006062   .0899846   -11.18   0.000    -1.182429   -.8296957
-------------+----------------------------------------------------------------
Wx           |
   logrealmw |    .177353   .1455446     1.22   0.223    -.1079092    .4626152
loglagrealmw |  -.1289434   .1083653    -1.19   0.234    -.3413355    .0834487
       loghs |  -.0052061   .1053096    -0.05   0.961    -.2116092    .2011969
  logcollege |   .0988331   .0559543     1.77   0.077    -.0108354    .2085015
      logpop |   .6727621   .1933257     3.48   0.001     .2938508    1.051673
      loggdp |  -.5628967   .2596894    -2.17   0.030    -1.071879   -.0539148
     logprod |   .5364926   .2488869     2.16   0.031     .0486833    1.024302
-------------+----------------------------------------------------------------
Spatial      |
         rho |   .1333972   .0772801     1.73   0.084    -.0180691    .2848635
-------------+----------------------------------------------------------------
Variance     |
    sigma2_e |   .0013607   .0002243     6.07   0.000      .000921    .0018004
-------------+----------------------------------------------------------------
SR_Direct    |
   logrealmw |  -.1380869   .0550549    -2.51   0.012    -.2459925   -.0301814
loglagrealmw |   .0800526   .0412876     1.94   0.053    -.0008696    .1609748
       loghs |  -.1089771   .0523142    -2.08   0.037    -.2115111   -.0064431
  logcollege |  -.0411118   .0198492    -2.07   0.038    -.0800156   -.0022081
      logpop |  -.3357686   .1186676    -2.83   0.005    -.5683529   -.1031843
      loggdp |   .9775235   .1037488     9.42   0.000     .7741796    1.180867
     logprod |  -.9971035   .0874844   -11.40   0.000     -1.16857   -.8256373
-------------+----------------------------------------------------------------
SR_Indirect  |
   logrealmw |   .1704475   .1635648     1.04   0.297    -.1501337    .4910287
loglagrealmw |  -.1263678   .1234965    -1.02   0.306    -.3684165    .1156809
       loghs |  -.0279886    .114148    -0.25   0.806    -.2517145    .1957373
  logcollege |   .1077805   .0666324     1.62   0.106    -.0228167    .2383776
      logpop |   .7077182   .2437262     2.90   0.004     .2300237    1.185413
      loggdp |  -.4864988   .2959097    -1.64   0.100    -1.066471    .0934736
     logprod |   .4553418   .2817799     1.62   0.106    -.0969366     1.00762
-------------+----------------------------------------------------------------
SR_Total     |
   logrealmw |   .0323606    .193925     0.17   0.867    -.3477255    .4124467
loglagrealmw |  -.0463152   .1467272    -0.32   0.752    -.3338952    .2412648
       loghs |  -.1369657   .1353617    -1.01   0.312    -.4022697    .1283383
  logcollege |   .0666686   .0734777     0.91   0.364    -.0773451    .2106824
      logpop |   .3719496   .3191983     1.17   0.244    -.2536676    .9975669
      loggdp |   .4910247   .3686951     1.33   0.183    -.2316044    1.213654
     logprod |  -.5417618   .3247287    -1.67   0.095    -1.178218    .0946947
-------------+----------------------------------------------------------------
LR_Direct    |
   logrealmw |  -.1782951   .0719692    -2.48   0.013    -.3193521   -.0372381
loglagrealmw |   .1029545   .0540598     1.90   0.057    -.0030009    .2089098
       loghs |  -.1417304    .068313    -2.07   0.038    -.2756213   -.0078394
  logcollege |  -.0523573   .0259302    -2.02   0.043    -.1031795   -.0015351
      logpop |  -.4295871   .1556824    -2.76   0.006    -.7347191   -.1244551
      loggdp |   1.264475   .1364494     9.27   0.000     .9970396    1.531911
     logprod |  -1.290258   .1146382   -11.26   0.000    -1.514944   -1.065571
-------------+----------------------------------------------------------------
LR_Indirect  |
   logrealmw |   .2181034   .2245681     0.97   0.331     -.222042    .6582489
loglagrealmw |  -.1652417   .1692888    -0.98   0.329    -.4970417    .1665583
       loghs |  -.0452704   .1559706    -0.29   0.772    -.3509673    .2604264
  logcollege |   .1441967    .092079     1.57   0.117    -.0362748    .3246681
      logpop |   .9405098   .3421913     2.75   0.006     .2698272    1.611192
      loggdp |  -.6021628   .3991603    -1.51   0.131    -1.384503     .180177
     logprod |   .5577977   .3772176     1.48   0.139    -.1815351    1.297131
-------------+----------------------------------------------------------------
LR_Total     |
   logrealmw |   .0398083   .2655799     0.15   0.881    -.4807187    .5603353
loglagrealmw |  -.0622872   .2007483    -0.31   0.756    -.4557467    .3311722
       loghs |  -.1870008   .1859583    -1.01   0.315    -.5514723    .1774707
  logcollege |   .0918394   .1018197     0.90   0.367    -.1077236    .2914023
      logpop |   .5109227   .4439137     1.15   0.250    -.3591322    1.380978
      loggdp |   .6623126   .4978059     1.33   0.183     -.313369    1.637994
     logprod |    -.73246   .4369807    -1.68   0.094    -1.588926    .1240064
------------------------------------------------------------------------------

.
I am confused as to why the results say "convergence not achieved".
When I omit time fixed effects, the results are okay, but R-sq actually increased which is strange.
I also don't actually want to omit time fe because I believe there are time effects which may influence the employment levels. When I use standard fixed effects estimation (not a spatial model) and test for the joint significance of the time dummies, the results show that they are jointly significant. So, I would like to keep the time fixed effects in my model.

My questions are:
1. are the above results reliable (despite having the "convergence not achieved" message)?
2. What can I do to obtain convergence? I have tried the option "difficult" but nothing happened.


Any inputs, comments, and suggestions would be greatly appreciated.

Thank you so much in advance,
Tifani