TFP in R via estprod package
In order to get coefficient for the materials in the Levinsohn-Petrin model you need to set the gross option true.
 mod1LP = estprod::levinsohn_petrin(data = DataA, va ~ l | k | m, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = TRUE, gross = TRUE)
     summary(mod1LP)

    Call
estprod::levinsohn_petrin(data = DataA, formula = va ~ l | k | 
    m, gross = TRUE, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = TRUE)

Coefficients
   Estimate Std. Error z value  Pr(&gt;|z|)    
l 0.1033754  0.0067384  15.341 &lt; 2.2e-16 ***
k 0.5859219  0.0048667 120.394 &lt; 2.2e-16 ***
m 0.4808831  0.0143580  33.492 &lt; 2.2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

#Bootstraped standard errors.

The other two functions unfortunately don't collect the coefficients for proxy variables.
An alternative is to find some different proxy and use $m$ as a control (I do not necessarily endorse such option from scientific perspective but if you are hell bent on having coefficient for $m$ its an option). In your dataset you don't have any additional variables beside $l$, $k$ and $m$ (aside from COGS that is always N/A) so I will just create a new variable to show it would work:
 DataA$m2&lt;-(DataA$m)^2

mod1OP = estprod::olley_pakes(data = DataA, va ~  l |  k | m2 |  m, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = TRUE, gross = TRUE)
 summary(mod1OP)
 
     
    Call
estprod::olley_pakes(data = DataA, formula = va ~ l | k | m2 | 
    m, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = TRUE, 
    gross = TRUE)

Coefficients
    Estimate Std. Error z value  Pr(&gt;|z|)    
l  0.1057613  0.0040007 26.4360 &lt; 2.2e-16 ***
k  0.4643984  0.0308697 15.0438 &lt; 2.2e-16 ***
m -0.0458770  0.0048684 -9.4234 &lt; 2.2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

#Bootstraped standard errors.
 


   mod1W = estprod::wooldridge(data = DataA, va ~ l | k | m2 | m, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = FALSE, gross = TRUE)
     summary(mod1W)

Call
estprod::wooldridge(data = DataA, formula = va ~ l | k | m2 | 
    m, gross = TRUE, id = &quot;ID&quot;, time = &quot;Year&quot;, bootstrap = FALSE)

Coefficients
   Estimate Std. Error t value  Pr(&gt;|t|)    
l 0.1210159  0.0075386  16.053 &lt; 2.2e-16 ***
k 0.4670722  0.0135809  34.392 &lt; 2.2e-16 ***
m 0.2595440  0.0158134  16.413 &lt; 2.2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Again such course of action does not seem to make sense to me but it gives you the desired output.