An Overview of Laboratory Research on Conservation Auctions Steven Schilizzi Steven.Schilizzi@uwa.edu.au Centre for Environmental Economics and Policy (CEEP) First landmarks • First theoretical paper on C.A. in AJAE, 1997 • First experimental paper on C.A. in JEEM, 2003 • Just over 5 years between them • Both in top ranked journals • Slow beginning… but recent acceleration! Laboratory studies of conservation auctions in the last decade (cumulative) Laboratory studies of conservation auctions in the last decade (per year) Main publishing journals (by frequency) • Land Economics • AmJAE • Ecol Econ > 25% of papers yet unpublished in 2013 Also the following journals: • JEEM • EaRE • AJARE This overview not just published papers Organization of overview I. Issues and questions addressed II. Key insights and contributions III. Pending questions and unresolved problems I/ Issues and questions addressed • Auction institution design Choice of auction format Auction implementation rules • Bidders Bidder characteristics Bidder behaviour • Auction performance evaluation Evaluation criteria Performance evaluations Auction institution design (1) Choice of auction format, in relation to to bidder behaviour: • • Indirectly : adverse selection; competition intensity; sequential entry Directly : individual / group bids; LDCs / DCs; crowding out potential to the bids themselves: • Sequential auctions; iterated bidding; multi-unit bids; combo bids; agglomeration bonuses; P vs Q bids to the distribution of information: • • In multi-round, number of rounds known ex-ante or not Neutral vs contextualized auction setting to payment rules: • DP vs UP; BC vs TC; linking payments to outcomes Auction institution design (2) Auction implementation rules, in relation to The distribution of information • Communication between bidders; • type/amount of info provided by auctioneer Payment rules (once format is chosen) • • • • If UP, first rejected vs last accepted price In iterative bidding, use of lock-in rule Auctioneer’s reserve price Imposed payment rule or ex-ante chosen by bidders Transaction costs Bidders Bidder characteristics Bidder heterogeneity Endowment bias Bidder behaviour Bidder learning (but not auctioneer’s learning) • effects on DP vs UP, BC vs TC, P vs Q performance Bidder risk aversion • Effects on outcome-linked payments Bid shading (or rent-seeking) Imperfect compliance & moral hazard Role of social networks & group leaders in belief format’n Trust, reciprocity & non-selfish prefs in repeated auctions II/ Key insights and contributions Auction format (1) • DP vs UP DP > UP in ‘standard’ lab settings, but: Not robust to • • • rate of bid shading, bidder heterogeneity (in costs & risk aversion), post-contracting compliance (moral hazard),… UP > DP if goal is to learn about compliance costs • BC > TC in repeated auctions (less bidder learning) • Q > P bids in repeated auctions (less learning) • ‘Dynamic entry’ more efficient scoring metrics… (insights, cont’d) Auction format (2) • Linking payments to uncertain outcomes Either do so without auctioning, or auction but not do so But srongly depends on what performance metric is used • Iterated bidding Benefit: Greater efficiency in earlier rounds (then eroded by learning) Can permit better coordination at landscape level Cost: Greater transaction costs for auctioneer • Capturing site-synergies Strongly depend on indiv vs group bids, communic. Agglom bonus better offers, spatial targeting best parcels selected • Potential for crowding out = serious ! (insights, cont’d) Implementation rules (1) • Information provision (by auctioneer) on envir. benefits, on aggreg/contiguity benefits improves auction’s cost-effic. on the (implicit) reserve price bidder confusion and ‘auction failure’ (target not met) less info (uncertainty) on bidders’ own opport. costs reduced participation; bids & auct perf more volatile • Info transmission (between bidders) strong ‘demand’ for communic’n by bidders collusion but also sharing of benefits ( cooperat’n) • Feedback in iterative bid collusion & cooperat’n (insights, cont’d) Implementation rules (2) • Feedback in iterative bid collusion & cooperat’n • Group leaders and social networks: leaders beliefs, collusion, more rents networks opposite effect if group-perf’ce incentives (insights, cont’d) Bidder characteristics • Cost heterogeneity impacts DP vs UP • Steep cost curves UP > DP , but… • Very steep curves auction not best approach (?) - (nor very flat curves) • Productivity heterogeneity (for outcome pay’ts) Knowledge of type affects participation and bidding But interacts in complex ways with risk aversion • Endowment bias WTA for A does depend on how much of B a bidder has (insights, cont’d) Bidder behaviour • Learning (in repeated auctions) Bidder learning is greater in TC and P than in BC and Q … but knowledge of auction format (e.g. DP vs UP) matters Can erode auction perf’ce to < {fixed price scheme} • Bid shading: theoretical predictions confirmed, but Over-bid-shading by low cost bidders not constant E.g. hockey stick in agriculture but logit shape in fisheries Neuro-economic studies have started to investigate • Risk aversion impacts (in complex ways) on DP vs UP performance Participation, bidding and resulting auction performance • Imperfect compliance impacts DP vs UP (DP = more adv selectn) III/ Pending questions and unresolved problems Auction performance evaluation • Role of experimental parameterizations in results • Multiplicity of evaluation criteria trade-offs • Performance (outcome) metrics: problematic, imprecise knowledge of which can affect bidding behaviour • Weight of transaction costs (often not measured) Value of (framed) field experiments (Pending questions, cont’d) Auction format and implementation rules • • • • • • • • • • • Role of contextualization (vs. neutral framing) (Potential) political hurdles for UP auctions Impact of duration or permanence of conserv’n contract Role of multiple rounds in iterated-bidding auctions Role of different types of uncertainty (costs, competition…) Presence of common-value elements (winner’s curse) Site synergies with more realistic configurations More realistic auctions with outcome-linked payments Specific impacts of different shapes of cost curve Specific impacts by type of information provided/withheld Auctions distributional outcomes and equity preferences (Pending questions, cont’d) Bidder characteristics and behaviour • Impacts of bidder heterogeneity, with some realism In costs, risk attitudes, equity prefs, endowments… • Using students for field extrapolations (lab vs artefactual) • Little understanding of how bidders form expectations • What exactly is ‘bidder learning’? Different types? • Auctioneer’s learning and choice of auction format etc. • Conservation auctions run by non-government agents? • Role of social networking; pre-existing vs formed groups • Role of group- or joint bidding (& combinatorial bids) Conclusion : taming conservation auctions via an epistemological reversal? • Conservation auctions are very complex! • We may never understand them completely… …if we hold on to the old analytical view • “Context” (auction’s environment) may be the key Vary context systematically and observe outcomes … … specifying institutional & regulatory ‘implementation conditions’ • Field studies to inform on the “implementation conditions” • = Complete reversal of traditional approach • Not just for conservation auctions – for much of economics Danke für Ihre Aufmerksamkeit Thank you for your attention