I am a very new R user. And for a project I need to estimate a "Semiparametric smooth-coefficient (SPSC)' model. I have been reading some published papers (including this one ) and R help files. However, I need help to know how to estimate the model.

Specifically, I have cross-section data on 1,000 households. The dependent variable is gross returns, which is a function of land and labor inputs. In addition, I have 3 risk-related variables that enter the production function in some unspecified nonlinear way. The related paper that I am following is attached.

`Returnsi = α(Zi) + Landiβ1(Zi) + Laboriβ2(Zi) + ui *, i = 1 , · · · , n,`

Where Z specifies the 3 risk related variables.

In terms of coding I have only got to the part where I have loaded my data and tried to use the ‘np’ library

install.packages(c("readxl", "np"))

library(readxl)

library(np)

Data=read_excel("C:/Users/Aaisha/Desktop/Data.xlsx")

head(Data)

str(Data)

Data$log_output <- log(Data$gross_inc_freshproduce)

Data$log_land <- log(Data$land_veg )

Data$log_labor <- log(Data$Labour_no )

spsc_model <- npscoef(log_output ~ log_land + log_labor | risk_behavior + risk_pref + agt_exper , data = Data)

I would appreciate any suggestions to estimate the SPSC model in R.