Quantifying Search and Switching Costs in the U.S. Auto Insurance Industry

Honka, Elisabeth

doi:10.2139/ssrn.2023446

Cited by 50 publications

(84 citation statements)

References 45 publications

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“…Hong and Shum [2006], Hortacsu and Syverson [2004] and Moraga-Gonzalez and Wildenbeest [2008] are early attempts that utilize aggregate market level data, and more recent efforts by e.g. Kim et al [2011], De Los Santos et al [2012], De Los Santos et al [2013], Honka [2014], Koulayev [2014] and utilize detailed consumer level data on both choices and the search process/consideration sets (as obtained, e.g., from website clicks) to test and estimate models of consumer search. Our empirical setting is one where we observe the choices of consumers, but do not observe their search process/consideration sets.…”

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confidence: 99%

Power to Choose? An Analysis of Consumer Inertia in the Residential Electricity Market

Hortaçsu

Madanizadeh

Puller

2015

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Many jurisdictions around the world have deregulated utilities and opened retail markets to competition. However, inertial decisionmaking can diminish consumer benefits of retail competition. Using householdlevel data from the Texas residential electricity market, we document evidence of consumer inertia. We estimate an econometric model of retail choice to measure two sources of inertia: (1) search frictions/ inattention, and (2) a brand advantage that consumers afford the incumbent. We find that households rarely search for alternative retailers, and when they do search, households attach a brand advantage to the incumbent. Counterfactual experiments show that low-cost information interventions can notably increase consumer surplus.

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confidence: 99%

Power to Choose? An Analysis of Consumer Inertia in the Residential Electricity Market

Hortaçsu

Madanizadeh

Puller

2015

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“…10 Such an identification result would not be very useful from a practical point of view if preferences of decision-makers were not identifiable. Therefore in this Section we focus on the joint identification of preferences and search costs.…”

Section: Joint Identification Of Preferences and Search Costsmentioning

confidence: 99%

“…In this type of markets, we study whether the econometrician can identify the search cost distribution nonparametrically using market shares data and knowing the utility distributions a large number of options provide to the decision-makers. We first show that such data from a single market do 1 See e.g., Mehta, Rajiv, and Srinivasan (2003), Hortaçsu and Syverson (2004), Hong and Shum (2006), Kim, Bronnenberg and Albuquerque (2009), Honka (2010), Koulayev (2010), Moraga-González, Sándor, and Wildenbeest (2010) and Seiler (2010). not provide sufficient information to identify the costs of simultaneous search in any reasonable interval.…”

Section: Introductionmentioning

confidence: 99%

On the Identification of the Costs of Simultaneous Search

2010

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This paper studies the identification of the costs of simultaneous search in portfolio problems (Chade and Smith, 2006). We show that market shares data from a single market do not provide sufficient information to identify the search cost distribution in any interval, even if utility distributions are known to the econometrician. We then show that by pooling data from markets where the alternatives that similar decision makers confront vary, the search cost distribution and the utility parameters of the logit demand model can be identified.

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“…auto insurance industry Honka (2013) estimates an average switching cost of $116, while in the U.S. pay-TV market Shcherbakov (2009) estimates switching costs of $109 for cable and $186 for satellite. These amount to respectively 20%, 32% and 52% of what a typical consumer would spend annually on these products.…”

Section: Introductionmentioning

confidence: 99%

Re-examining the effects of switching costs

Rhodes

2014

Econ Theory

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Consumers often incur costs when switching from one product to another.Recently there has been renewed debate within the literature about whether these switching costs lead to higher prices. We build a theoretical model of dynamic competition and solve it analytically for a wide range of switching costs.We provide a simple condition which determines whether switching costs raise or lower long-run prices. We also show that switching costs are more likely to increase prices in the short-run. Finally switching costs redistribute surplus across time, and as such are shown to sometimes increase consumer welfare.

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Quantifying Search and Switching Costs in the U.S. Auto Insurance Industry

Cited by 50 publications

References 45 publications

Power to Choose? An Analysis of Consumer Inertia in the Residential Electricity Market

Power to Choose? An Analysis of Consumer Inertia in the Residential Electricity Market

On the Identification of the Costs of Simultaneous Search

Re-examining the effects of switching costs

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