Clicks and Mortar Efficiency and the Internet Price Discrimination • Uniform versus non-uniform pricing – Possibility of arbitrage Uniform pricing • Uniform pricing is linear pricing – Tariff T(q)=pq – Distribution of surplus and efficiency • Types of price discrimination – First degree • Seller extracts full surplus – Second degree • Partial discrimination based on buyer self-selection into pricing category – Third degree • Discrimination based on signal correlated with preference Price Discrimination • First degree discrimination – Charge each customer her maximum willingness to pay • Extracts total social surplus from the market • Resulting allocation is efficient: – Let p(q) be the inverse demand function. Then the monopolist receives p(q) for the q th unit sold. This the monopolist’s marginal revenue. Profit maximization requires that the monopolist produce and sell to the point where MR=MC. But this is the same condition that determines the competitive equilibrium allocation which is efficient. – Implementation in monopoly market by two-part tariff • Let Sc be the competitive consumer surplus Price Discrimination • Graphically: Price Discrimination • Suppose there are n buyers each of whom has the same demand schedule. • The monopolist offers a two-part tariff of the form • The profit per unit sold is then where C’(q) is the monopolist’s marginal cost Price Discrimination • Total profit is obtained by integrating the marginal profit with respect to q: But this is just the total surplus in the market. – It is straightforward to show that the profit the monopolist obtains exceed what she would have gotten at the uniform monopoly price. • Difficulties with implementing first-degree discrimination – Lack of knowledge about demand – Heterogeneity of demand Price Discrimination • Second-degree price discrimination – Applicable when buyers are heterogeneous and seller has limited information about preferences – Uses a menu of non-linear tariffs to allow buyers to self-select into a pricing scheme (personalized pricing) • Two-part tariff is a simple example of non-linear pricing scheme • Digital goods implementation in the form of versioning Price Discrimination – Tie-in Sales • Bundling of complementary goods or services leads naturally to a two-tier pricing system – Cameras and film – Amusement parks and rides – Online news subscriptions and access to archived material – Information tracking and analysis capabilities of the web • Flip side of targeted advertising – Track buyer preferences – Conduct price sensitivity experiments – Structure pricing tariffs according to data collected • Dark Side: Privacy Issues Price Discrimination • Third-degree price discrimination – Monopolist is able to segment the market using external signals about buyer types • Signals: – Age – Sex – Occupation – Location (or referring site) – New vs. repeat purchases – The monopolist then sets a uniform price in each market segment to maximize profits from each segment. Price Discrimination – Model • N market segments • pi = price in segment i, qi = quantity sold in segment i • Di(pi) = segmented demand function • q = i Di(pi) • Assuming a uniform cost function across segments, the monopolist’s profit maximization is then to choose prices for each market segment to solve the problem Price Discrimination • The first-order conditions for this problem can be manipulated into the form The optimal pricing rule then is for the monopolist to set the markup over marginal cost (as a percentage of the price) equal to the inverse of the elasticity of demand. Price Discrimination • Some implications of the markup rule – Market segments with higher demand elasticity will receive a lower price Greater price sensitivity market segments get lower prices – Conversely, segments which are less price sensitive will pay higher prices – Welfare analysis for simple cases shows that the overall effects of market segmentation are ambiguous. Depending on how price sensitive different segments are relative to each other, overall consumer surplus may be larger or smaller with discrimination than without Price Discrimination • Privacy Issues – Sensitivity of personal information • Medical information and insurance • Access to credit • Protection from job actions • Exposure to spam • Exposure to price discrimination – Information value-added • Customization of products • Targeting of useful information about products • Simplification of transactions Price Discrimination – The myth of anonymity Price Discrimination – Internet communications • Complexity of communication protocols requires tracking information • Packet switching – Message fragmented into uniform size packets – Headers encode information about packet destination using the internet protocol (IP) address of the recipient – Packets routed through network under control of network transmission control protocol (TCP) » TCP checks for errors in packets and will request retransmission of bad packets packets can be traced – Message reconstructed as packets reach destination • Cookies • Internet communication is anything but anonymous Price Discrimination – Protecting content while revealing identity • Encryption – Secure communications – Online payment systems – Digital signatures – Trust relationships • Legal protections – Privacy guarantees and the First Amendment (freedom of speech) and Fourth Amendment (freedom from unlawful searches) – Legal restrictions on distribution of personal information disclosed in transactions – “Truth in advertising” enforcement of pledges to protect customer privacy by firms Price Discrimination – Market mechanisms for privacy protection • Service for information arrangements – Email – Search – Online file storage – Data analysis engines • Trust relationships – Trusted independent intermediary verifies content and claims – Provision for legal intervention by violators » “Better business bureau” model Intermediation • Economic role of intermediaries – Transactional efficiencies • Lower costs in inventory holding, product delivery, insurance, financing, accounting • Inventory and demand issues • The internet as an information aggregator and transactional role for intermediaries in markets for digital goods – Intermediaries as Experts • Repeat purchases – Incentive to acquire knowledge about product • Intermediary as Long-term Player – Ongoing benefit to credibility Intermediation • Intermediaries as information sources – Long-term, multi-product intermediaries and “reputational spillovers” • Intermediary has incentive to ensure high quality in any given product to avoid lost sales in other, unrelated products • Intermediary role provides a “punishment mechanism” in the form of exclusion of a seller’s product if quality lags • Intermediate production activities – Combining of separate products in “retail bundles” – Particularly germane in the information industry • News and entertainment content providers combine, package and distribute work of individual authors • CNN, Napster Auctions and Contracts • Market Efficiency and Competition – Contracts versus Auctions • Auctions are competitive but costly to hold when all parties to the transaction must be present in the same place and time to participate • Contracts are negotiated bilaterally – Less information about costs – Less competitive pricing (Ford-Autolite example) – Less flexibility if terms change – Lower cost since contract governs relationship for an extended period of time Auctions and Contracts • Auction Types – Direct vs. Reverse – English vs. Dutch – Sealed bid vs. open outcry • Vickery’s Theorem – If buyers have the same information about an object being sold, are risk-neutral, and have independent valuations of the object, then any of the above auction formats will achieve maximum revenue for the seller. – Key points: • Uncertainty about value • Independence of valuations Auctions and Contracts • Common value auctions – Most common type of auction – Valuations are unknown but closely (or perfectly) correlated • Example: Offshore oil tracts • Example: Procurement contracts for manufactured intermediate products • The Winner’s Curse – Experiment: Auctioning off a jar of money • Format – Sealed Bid – First price (i.e. highest price wins) Auctions and Contracts • Information and the Winner’s Curse – Distribution of guesses – Mean guess as best estimate of actual value Auctions and Contracts – Since the winning bid must be higher than the mean (unless all bids are at the mean), if the mean is an accurate estimate of the true value, then the winning bid necessarily overstates the value of the object at auction, and the winner ends up paying too much for the object. – Optimal bid when faced with the winner’s curse? • Shave bids below what you believe the true value to be • Reduces revenue to the seller Auctions and Contracts • Reducing the risk of the Winner’s curse – Second-price auction • Highest bid wins, but pays second highest price • Eliminates incentive to shave bids – Open outcry auctions • Allows sharing of information among bidders as to the best guess of the true value of the object • Multi-object auctions – Discriminatory vs. Uniform – Potential inefficiencies in sequential auctions Auctions and Contracts • Example: 2 units to be auctioned – Buyer 1 values one unit at 10 and 2 at 20 – Buyer 2 values one unit at 9 and 2 at 10 – Simultaneous auction of both units • Buyer 1 wins with a bid of 10 – Sequential auction: Backward induction • Suppose Buyer 1 wins in round 1 • To win round 2, Buyer 1 must bid at least 9 • Moving back to round 1, since Buyer 2 values one unit at 9, for Buyer 1 to win round 1, she must bid at least 9. • Buyer 1’s profit from this is 20-9-9=2. Auctions and Contracts • Now, suppose Buyer 1 loses in first round. • Buyer 1 can win in round 2 with a bid of 1, yielding a profit of 10- 1=9. Hence, Buyer 1 is better of losing in round 1. • Knowing this, Buyer 2 can win round 1 with a bid of 2. To see why, we note the following: – Buyer 1 can get a profit of 9 by losing round1 and winning round 2. Hence, her maximum round 1 bid, if she wins, must yield profit at least equal to what she gets if she loses, i.e. 9. – Letting this bid be x, we need 20-9-x=9 or x=2 and buyer 2 can win in round 1 with a bid of 2 • Revenue from the sequential auction is then 2+1=3 so the sequential auction is clearly inefficient.