Simulated Maximum Likelihood Estimation of Weitzman's Sequential Search Model
This webpage shares the Matlab script that estimates the sequential search model by Weitzman (1979).
Settings:
Consumers search through products to resolve the uncertainty in the normally distributed match values.
Consumers make the search and purchase decision by Weitzman (1979)'s sequential search algorithm.
For each search, consumers incur a search cost that is assumed to follow an exponential distribution.
Search cost is assumed to vary at the consumer-product level and to be unobserved by researchers.
What the script does:
"main_for_loop.m" file and "main_vectorize" file simulate the product characteristics and the search and purchase decisions by 1,000 consumers and estimate the sequential search model by Weitzman.
Instruction:
Download and extract the zip file below. Run "main_for_loop.m" file or "main_vectorize" file.
"main_for_loop.m" utilizes for-loop to construct the simulated likelihood.
"main_vectorize" executes pre-computation to vectorize the likelihood function evaluation and remove the for-loop.
Note:
"search_function" folder needs to be placed in the same directory as "main_for_loop.m" script and "main_vectorize" file.