Choosing the wrong theoretical model to describe an industry’s behavior may lead to biased estimates of the degree of market power. This paper presents a two-step, data-driven methodology to reduce the risk of mis-specification bias. In the first step, a sliced inverse regression identifies the significant factors that affect the industry’s pricing behavior. In the second step, a non-parametric regression of price on the SIR factors estimates the link functions. The output of the algorithm offers useful information to identify the model that best approximates the industry’s pricing behavior. In addition, the output of the algorithm is used to develop a post-estimation test for model specification.
Review of Industrial Organization – Springer Journals
Published: Jan 17, 2012
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera