################################################################### # # Script for Replication of: Consumers' Preference and Willingness to Pay # For Biofortified Garri # Description: The script to estimate full attendance mixed logit model for ## nutrition treatment ## Author: Akinwehinmi Titilayo #################################################################### # # ################################################################# # #### LOAD LIBRARY AND DEFINE CORE SETTINGS #### # ################################################################# # ### Clear memory #rm(list = ls()) ### Load Apollo library check.packages <- function(pkg){ new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])] if (length(new.pkg)) install.packages(new.pkg, dependencies = TRUE) sapply(pkg, require, character.only = TRUE) } packages <- c("apollo", "lmtest", "dplyr", "tidyr", "tibble", "skimr", "gtsummary", "segmented", "ggplot2", "tidyverse", "hrbrthemes", "viridis") check.packages(packages) ### Initialise code apollo_initialise() ### Set core controls apollo_control = list( modelName = "Nutrition_Full_Attendance_Model", modelDescr = "Full Attendance Mixed logit model for Nutrition Treatment", indivID = "id", mixing = TRUE, nCores = 7, analyticGrad = TRUE, # Needs to be set explicitly for models with inter-intra draws (requires extra RAM). outputDirectory = "output" ) # ################################################################# # #### LOAD DATA AND APPLY ANY TRANSFORMATIONS #### # ################################################################# # ### Loading data from package ### if data is to be loaded from a file (e.g. called data.csv), ### the code would be: database = read.csv("data.csv",header=TRUE) #apollo_database = read.csv("data_biofortification.csv",header=TRUE) apollo_database = read.csv("data_biofortification.csv") #Subset database for Nutrition Group database <- subset(apollo_database, consumer==2) # ################################################################# # #### DEFINE MODEL PARAMETERS #### # ################################################################# # ### Vector of parameters, including any that are kept fixed in estimation apollo_beta = c( b_price = 0, #sigma_price_inter = 0, asc3 = 0, sigma_asc3_inter = 0, va = 0, sigma_va_inter = 0, iron25 = 0, sigma_iron25_inter = 0, iron50 = 0, sigma_iron50_inter = 0, lowstarch = 0, sigma_lowstarch_inter = 0, gm = 0, sigma_gm_inter = 0, ge = 0, sigma_ge_inter = 0, # # Correlation in preferences within the control group sigma_va_iron25 = 0, sigma_va_iron50 = 0, sigma_va_lowstarch = 0, sigma_va_gm = 0, sigma_va_ge = 0, sigma_iron25_iron50 = 0, sigma_iron25_lowstarch = 0, sigma_iron25_gm = 0, sigma_iron25_ge = 0, sigma_iron50_lowstarch = 0, sigma_iron50_gm = 0, sigma_iron50_ge = 0, sigma_lowstarch_gm = 0, sigma_lowstarch_ge = 0, sigma_gm_ge = 0 ) ### Vector with names (in quotes) of parameters to be kept fixed at their starting value in apollo_beta, use apollo_beta_fixed = c() if none apollo_fixed = c() ### Overwrite beta starting values #apollo_readBeta(apollo_beta, apollo_fixed, "Biofortification_July_WTP_Corr_ST_1", overwriteFixed = FALSE) # ################################################################# # #### DEFINE RANDOM COMPONENTS #### # ################################################################# # ### Set parameters for generating draws apollo_draws = list( interDrawsType = "sobol", interNDraws = 500, interUnifDraws = c("draws_price_inter", "draws_price_inter_a", "draws_price_inter_b"), interNormDraws = c( "draws_asc3_inter", "draws_va_inter", "draws_iron25_inter", "draws_iron50_inter", "draws_lowstarch_inter", "draws_gm_inter", "draws_ge_inter", #draws for correlation "draws_va_iron25" , "draws_va_iron50" , "draws_va_lowstarch" , "draws_va_gm" , "draws_va_ge" , "draws_iron25_iron50" , "draws_iron25_lowstarch" , "draws_iron25_gm" , "draws_iron25_ge" , "draws_iron50_lowstarch" , "draws_iron50_gm" , "draws_iron50_ge" , "draws_lowstarch_gm" , "draws_lowstarch_ge" , "draws_gm_ge" ) ) ### Create random parameters apollo_randCoeff = function(apollo_beta, apollo_inputs){ randcoeff = list() #Triangular #randcoeff[["b_price"]] = (price + price*(draws_price_inter_a+draws_price_inter_b)/2) #randcoeff[["b_price"]] = -exp(price + sigma_price_inter*draws_price_inter) randcoeff[["b_asc3"]] = (asc3 + sigma_asc3_inter*draws_asc3_inter) randcoeff[["b_va"]] = (va + sigma_va_inter*draws_va_inter) randcoeff[["b_iron25"]] = (iron25 + sigma_iron25_inter*draws_iron25_inter + sigma_va_iron25*draws_va_iron25) randcoeff[["b_iron50"]] = (iron50 + sigma_iron50_inter*draws_iron50_inter + sigma_va_iron50*draws_va_iron50 + sigma_iron25_iron50*draws_iron25_iron50) randcoeff[["b_lowstarch"]] = (lowstarch + sigma_lowstarch_inter*draws_lowstarch_inter + sigma_va_lowstarch*draws_va_lowstarch + sigma_iron25_lowstarch*draws_iron25_lowstarch + sigma_iron50_lowstarch*draws_iron50_lowstarch) randcoeff[["b_gm"]] = (gm + sigma_gm_inter*draws_gm_inter + sigma_va_gm*draws_va_gm + sigma_iron25_gm*draws_iron25_gm + sigma_iron50_gm*draws_iron50_gm + sigma_lowstarch_gm*draws_lowstarch_gm) randcoeff[["b_ge"]] = (ge + sigma_ge_inter*draws_ge_inter + sigma_va_ge*draws_va_ge + sigma_iron25_ge*draws_iron25_ge + sigma_iron50_ge*draws_iron50_ge + sigma_lowstarch_ge*draws_lowstarch_ge + sigma_gm_ge*draws_gm_ge) return(randcoeff) } # ################################################################# # #### GROUP AND VALIDATE INPUTS #### # ################################################################# # apollo_inputs = apollo_validateInputs() # ################################################################# # #### DEFINE MODEL AND LIKELIHOOD FUNCTION #### # ################################################################# # apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){ ### Function initialisation: do not change the following three commands ### Attach inputs and detach after function exit apollo_attach(apollo_beta, apollo_inputs) on.exit(apollo_detach(apollo_beta, apollo_inputs)) ### Create list of probabilities P P = list() ### List of utilities: these must use the same names as in mnl_settings, order is irrelevant V = list() V[["alt1"]] = (b_price*Price1 + b_va*VAB1 + b_iron25*IRA1 + b_iron50*IRB1 + b_lowstarch*LowStarch1 + b_gm*GM1 + b_ge*GE1 ) V[["alt2"]] = (b_price*Price2 + b_va*VAB2 + b_iron25*IRA2 + b_iron50*IRB2 + b_lowstarch*LowStarch2 + b_gm*GM2 + b_ge*GE2) V[["alt3"]] = (b_price*Price3 + b_asc3*asc33) ### Define settings for MNL model component mnl_settings = list( alternatives = c(alt1=1, alt2=2, alt3=3), avail = list(alt1=1, alt2=1, alt3=1), choiceVar = Choice, utilities = V ) ### Compute probabilities using MNL model P[["model"]] = apollo_mnl(mnl_settings, functionality) ### Average across intra-individual draws # P = apollo_avgIntraDraws(P, apollo_inputs, functionality) ### Take product across observation for same individual P = apollo_panelProd(P, apollo_inputs, functionality) ### Average across inter-individual draws P = apollo_avgInterDraws(P, apollo_inputs, functionality) ### Prepare and return outputs of function P = apollo_prepareProb(P, apollo_inputs, functionality) return(P) } # ################################################################# # #### MODEL ESTIMATION #### # ################################################################# # ### optionally load pre-estimated model from memory #model = apollo_loadModel("Biofortification_WTP_Stated_ANA_November_14_All_1A") # apollo_addCovariance(model, apollo_inputs) ### Optional speedTest # speedTest_settings=list( # nDrawsTry = c(100, 200, 500, 1000), # nCoresTry = 8, # nRep = 10) # apollo_speedTest(apollo_beta, apollo_fixed, apollo_probabilities, apollo_inputs, speedTest_settings) ### Optional starting values search # search_settings = list( # nCanditates = 10 # ) # apollo_beta=apollo_searchStart(apollo_beta, apollo_fixed,apollo_probabilities, apollo_inputs, search_settings) model = apollo_estimate(apollo_beta, apollo_fixed,apollo_probabilities, apollo_inputs, estimate_settings=list(maxIterations=400)) # ################################################################# # #### MODEL OUTPUTS #### # ################################################################# # # ----------------------------------------------------------------- # #---- FORMATTED OUTPUT (TO SCREEN) ---- # ----------------------------------------------------------------- # apollo_modelOutput(model) # ----------------------------------------------------------------- # #---- FORMATTED OUTPUT (TO FILE, using model name) ---- # ----------------------------------------------------------------- # apollo_saveOutput(model) # ################################################################# # ##### POST-PROCESSING #### # ################################################################# # ###Compute WTP from the Preference space estimates deltaMethod_settings=list(expression=c(wtp_va="va/(-b_price)", wtp_iron25="iron25/(-b_price)", wtp_iron50="iron50/(-b_price)", wtp_lowstarch="lowstarch/(-b_price)", wtp_gm="gm/(-b_price)", wtp_ge="ge/(-b_price)", wtp_sd_va="sigma_va_inter/(-b_price)", wtp_sd_iron25="sigma_iron25_inter/(-b_price)", wtp_sd_iron50="sigma_iron50_inter/(-b_price)", wtp_sd_lowstarch="sigma_lowstarch_inter/(-b_price)", wtp_sd_gm="sigma_gm_inter/(-b_price)", wtp_sd_ge="sigma_ge_inter/(-b_price)")) wtp_nutrition <- apollo_deltaMethod(model, deltaMethod_settings) write.csv(wtp_nutrition, "wtp_nutrition.csv")