# Synthetic control in julia

**URL:** <https://discourse.julialang.org/t/synthetic-control-in-julia/61615>\
**Category:** General Usage\
**Created:** [May 22, 2021, 12:38am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615 "2021-05-22T00:38:18Z")\
**Posts on this page:** 14\
**Page:** 1

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 22, 2021, 12:38am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/1 "2021-05-22T00:38:18Z")

</div>

Im currently trying to work through a question using synthetic control in r. link for context here: [https://economics.mit.edu/files/17847](https://economics.mit.edu/files/17847)

Ive found that the documentation is lacking and I have a syntax error. Has anyone put together a file to use synthetic control in julia?

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [May 22, 2021, 5:27am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/2 "2021-05-22T05:27:21Z")

</div>

I have the start of a package here [https://github.com/nilshg/SynthControl.jl](https://github.com/nilshg/SynthControl.jl) but I’ve shamefully neglected it over the last few months. It should work for getting a point estimate of the treatment effect out, but inference isn’t really operational (you can do permutation of placebos but have to process the results of the permutation yourself). Also it currently uses the pretreatment outcomes to find weights only, rather than Alfonso covariates like the originell Abadie et al paper.

Finally, the lady change I made was to spin out construction of the data object to go the estimation on into a separate `TreatmentPanel` type which I’m planning to use for other casual inference packages as well, and the readme doesn’t reflect this, so check the test file to see how you fit and plot the model.

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 22, 2021, 7:07pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/3 "2021-05-22T19:07:01Z")

</div>

First, thank you for putting this together.

but I’m having some trouble implementing it. I found the the test file and managed to get your example to work. However my code has an error that i dont understand. Could you help me?

```julia
julia> # format data so its easier to compare to example
       formatdata = DataFrame(state = mydata.name, year = mydata.year , Y = mydata.Y )
809×3 DataFrame
 Row │ state year Y         
     │ String Date Float64   
─────┼────────────────────────────────
   1 │ alabama 2000-01-01 5.27832
   2 │ alabama 2001-01-01 7.63268
   3 │ alabama 2002-01-01 6.51773
   4 │ alabama 2003-01-01 6.55047
   5 │ alabama 2004-01-01 5.58409
   6 │ alabama 2005-01-01 7.15567
   7 │ alabama 2006-01-01 7.73388
   8 │ alabama 2007-01-01 8.3889
   9 │ alabama 2008-01-01 7.24852
  10 │ alabama 2009-01-01 6.68357
  11 │ alabama 2010-01-01 3.99604
  12 │ alabama 2012-01-01 0.041532
  13 │ alabama 2013-01-01 0.0414039
  14 │ alabama 2014-01-01 0.0206506
  ⋮ │ ⋮ ⋮ ⋮
 797 │ wyoming 2005-01-01 3.30638
 798 │ wyoming 2006-01-01 1.72194
 799 │ wyoming 2007-01-01 3.36527
 800 │ wyoming 2008-01-01 2.01449
 801 │ wyoming 2009-01-01 2.14343
 802 │ wyoming 2010-01-01 1.41938
 803 │ wyoming 2011-01-01 3.52594
 804 │ wyoming 2012-01-01 2.95001
 805 │ wyoming 2013-01-01 2.92035
 806 │ wyoming 2014-01-01 2.40324
 807 │ wyoming 2015-01-01 3.07341
 808 │ wyoming 2016-01-01 3.9364
 809 │ wyoming 2017-01-01 2.41824

julia> # this is what i cant get to work
       tp = TreatmentPanel("colorado" => Date(2014), formatdata; outcome = :Y, id_var = :state, t_var = :year)
ERROR: DimensionMismatch("new dimensions (44, 14) must be consistent with array size 615")
Stacktrace:
 [1] (::Base.var"#throw_dmrsa#213")(::Tuple{Int64,Int64}, ::Int64) at ./reshapedarray.jl:41
 [2] reshape at ./reshapedarray.jl:45 [inlined]
 [3] reshape(::Array{Float64,1}, ::Int64, ::Int64) at ./reshapedarray.jl:116
 [4] TreatmentPanel(::Pair{String,Date}, ::DataFrame; outcome::Symbol, id_var::Symbol, t_var::Symbol, predictors::Nothing) at /Users/modelt/.julia/packages/SynthControl/nHELX/src/treatmentpanel.jl:117
 [5] top-level scope at REPL[10]:2

```

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 22, 2021, 7:38pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/4 "2021-05-22T19:38:42Z")

</div>

I wasnt sure if i needed to tag you in my reply

---

<div class="post-metadata">

**Author:** ![pdeffebach](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pdeffebach/32/10320_2.png) [@pdeffebach](https://discourse.julialang.org/u/pdeffebach)\
**Post date:** [May 22, 2021, 9:30pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/5 "2021-05-22T21:30:51Z")

</div>

FWIW, I’ve never been able to use Synthetic Control in R, also encountering indecipherable errors, but I’ve found Stata’s package to work well, if you have access to Stata.

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 22, 2021, 10:10pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/6 "2021-05-22T22:10:08Z")

</div>

I do have access, i suppose it will be my last resort.

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [May 22, 2021, 11:12pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/7 "2021-05-22T23:12:43Z")

</div>

Can you share the data? I’d be happy to really a look tomorrow -the error suggests something is going wrong in forming the matrix of pretreatment outcomes, which uses `reshape`.

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [May 22, 2021, 11:14pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/8 "2021-05-22T23:14:59Z")

</div>

Off the top of my head, is your panel balanced? I haven’t looked at the code on a while but I think it currently assumes a balanced panel, mainly because I didn’t know how to treat missing observations for some i/t combinations in the minimization step. So one thing you can try is restricting your data to have the same number of pretreatment periods for all observations.

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 23, 2021, 2:38am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/9 "2021-05-23T02:38:01Z")

</div>

Here is a link to my data. [GitHub - efhart4/Syntheticdata](https://github.com/efhart4/Syntheticdata)

If my treatment period is 2014, should i restrict data from 2010 to 2017 to balance the dataset?

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [May 23, 2021, 7:01am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/10 "2021-05-23T07:01:28Z")

</div>

Sorry I wasn’t exactly clear maybe - by balanced panel I mean that each unit of observation is observed in the same time periods. From your data I see that Alabama is missing one observation (all other states have 18 years in the data, Alabama only 17). The package internally builds a matrix of size `(n_control_units, n_pretreatment_periods)`, which doesn’t work if control units don’t have the same number of pretreatment outcomes.

If you exclude Alabama it works:

```julia
julia> tp = TreatmentPanel("colorado" => 2014, df[df.name .!= "alabama", :], outcome = :Y, id_var = :name, t_var = :year)
TreatmentPanel
  data: DataFrame
  outcome: Symbol Y
  id_var: Symbol name
  t_var: Symbol year
  treatment: Pair{Union{String, Symbol}, Union{Int64, Date}}
  y₁₀: Array{Float64}((14,)) [3.09689037539627, 3.41189966665062, 4.03081592176743, 4.19543483694774, 4.7212980596995, 3.82133592176667, 3.72847941805215, 3.35146594369371, 3.27216431173091, 3.3184539222617, 2.88316462512099, 3.26059091669659, 2.98437286099889, 3.52908899034282]
  y₁₁: Array{Float64}((4,)) [3.08341016942311, 3.4665497210528, 4.02460168625396, 4.14893279832875]
  yⱼ₀: Array{Float64}((43, 14)) [7.46039306388848 3.64459424983568 … 1.75225436285053 2.78619300619598; 8.36260402766524 3.72130409380663 … 1.75987869949795 3.20970259891833; … ; 2.58698745311085 1.30826593198556 … 2.60933747015937 2.95000607354192; 3.43348512728692 2.50007197176888 … 3.11916245120324 2.92034501299554]
  yⱼ₁: Array{Float64}((43, 4)) [4.64816508856759 4.63807710133236 2.25612353902884 8.56456115413491; 5.03395284122737 3.80565515825976 2.3988631474649 7.82536527615169; … ; 4.36500816978301 3.03268597015624 1.89306815234655 3.93640144448818; 3.4692846369428 3.33067760256769 6.86182014858432 2.41823765748773]
  x₁₀: Nothing nothing
  xⱼ₀: Nothing nothing
  predictors: Nothing nothing
  J: Int64 43
  T₁: Int64 4
  T₀: Int64 14
  comp_labels: Array{Union{String, Symbol}}((43,))

julia> s = SynthControlModel(tp)

Synthetic Control Model
	Outcome variable: Y
	Time dimension: year with 18 unique values
	Treatment period: 2014
	ID variable: name with 44 unique values
	Treatment ID: colorado

	Model is not fitted

julia> SynthControl.fit!(s)

Synthetic Control Model
	Outcome variable: Y
	Time dimension: year with 18 unique values
	Treatment period: 2014
	ID variable: name with 44 unique values
	Treatment ID: colorado
	Model is fitted
	Impact estimates: [-2.211, -2.506, -0.674, -0.451]

julia> using Plots

julia> plot(s)

```

produces:

![image](https://global.discourse-cdn.com/julialang/original/3X/8/3/83325f124be5cb78ebff83a6e703695a5c612693.png)

Now just based on gut feel that looks like a slightly surprising result, the jaggedness of the pre-treatment fit suggests to me that this might not survive inference if I got it to work 🙂

I also realize that the weigthplot that I thought I’d implemented seems not to work properly, but you can do

```julia
julia> weightdf = DataFrame(State = s.treatment_panel.comp_labels, Weight = s.w);

julia> bar(weightdf[weightdf.Weight .> 0.01, :State], weightdf[weightdf.Weight .> 0.01, :Weight], label = "Weight", xrot = 45)

```

to get

![image](https://global.discourse-cdn.com/julialang/original/3X/7/c/7c160829fa5c71db28ffae5b8b91d7ba8a761137.png)

So the weights aren’t exactly sparse, which can be a problem if one fits purely based on pre-trends I believe. I really should get covariates to work to help with this, but I probably won’t have time over the next weeks unfortunately…

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 23, 2021, 9:29am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/11 "2021-05-23T09:29:13Z")

</div>

thank you

---

<div class="post-metadata">

**Author:** ![Evan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/evan/32/25369_2.png) [@Evan](https://discourse.julialang.org/u/Evan)\
**Post date:** [May 23, 2021, 9:39am UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/12 "2021-05-23T09:39:13Z")

</div>

I wrote it up for r here

[https://stackoverflow.com/questions/67627348/synthetic-control-using-librarysynth-error-your-panel-as-described-by-unit-v/67658264#67658264](https://stackoverflow.com/questions/67627348/synthetic-control-using-librarysynth-error-your-panel-as-described-by-unit-v/67658264#67658264)

---

<div class="post-metadata">

**Author:** ![Albert\_Zevelev](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/albert_zevelev/32/11844_2.png) [@Albert\_Zevelev](https://discourse.julialang.org/u/Albert_Zevelev)\
**Post date:** [June 5, 2021, 6:45pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/13 "2021-06-05T18:45:57Z")

</div>

Hi @Evan, I wrote up Synthetic Control code in Julia to study the impact of foreign buyer taxes (15% in 2016, 20% in 2018) on house price growth in Vancouver.

I use Elastic Net (as argued in Doudchenko & Imbens), but you can easily modify my code to use your favorite ML model or ensemble…

I just created a Github repo w/ data & parsimonious code:  
[https://github.com/azev77/Synthetic\_Control\_in\_Julia](https://github.com/azev77/Synthetic_Control_in_Julia)

Goodluck!

---

<div class="post-metadata">

**Author:** ![Albert\_Zevelev](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/albert_zevelev/32/11844_2.png) [@Albert\_Zevelev](https://discourse.julialang.org/u/Albert_Zevelev)\
**Post date:** [June 5, 2021, 6:55pm UTC](https://discourse.julialang.org/t/synthetic-control-in-julia/61615/14 "2021-06-05T18:55:36Z")

</div>

Below are the four figures produced by my code.

1. Year over Year, house price growth in Vancouver:  
 ![image](https://global.discourse-cdn.com/julialang/original/3X/2/0/20f623cd8600a432f6d7695a25ed95766911d8a8.png)
2. Observed house price growth in Vancouver & counterfactual house price growth in “Synthetic Vancouver” if there was no foreign-buyer tax  
 ![image](https://global.discourse-cdn.com/julialang/original/3X/d/8/d8bbf64224be82da492426a64548706cfbf84759.png)
3. Unit placebo tests  
 ![image](https://global.discourse-cdn.com/julialang/original/3X/2/a/2a4d7030afadbe6ab01bd3dcd6384c10e7e9afdb.png)
4. The ATT (Average Treatment Effect on the Treated) w/ 95% CIs (using [Jackknife+](https://www.stat.cmu.edu/~ryantibs/papers/jackknife.pdf))  
 ![image](https://global.discourse-cdn.com/julialang/original/3X/e/d/edd4c0fb6f175f7e308b38c78c4362e7c002db89.png)

PS: I actually have code for [at least 8 inference methods for SCM](https://twitter.com/AlexZevelev/status/1367663893783453698) (all in Julia) stay tuned…