Illiquid Lemon Markets and the Macroeconomy
What this paper finds — and why it matters
The paper develops a quantitative capital-accumulation model in which capital trades in illiquid markets with asymmetric information — sellers know the quality of their capital but buyers do not. It combines this model with microdata on nonresidential capital units listed for trade to measure the degree of information asymmetry and quantify its macroeconomic effects.
Model: The economy features heterogeneous capital units characterized by observed quality ω (e.g., size, location, age — observable to both buyers and sellers) and unobserved quality a (known only to the seller). Capital trades in directed-search markets: sellers post a price and a target submarket; buyers direct their search; a matching function determines trade probabilities. Buyers observe announced quality and have an inspection technology that reveals true quality with probability ψ (“lemon detection probability”); with probability 1−ψ a low-quality unit goes undetected. In equilibrium, sellers of high-quality capital signal their type by listing at higher prices and accepting lower trading probabilities (the Guerrieri-Shimer-Wright 2010 competitive search separating equilibrium, adapted to the capital accumulation setting). The key model prediction is that the residual price — the component of a listed price orthogonal to observed characteristics — is positively correlated with duration on the market, with the slope increasing as the degree of asymmetric information (1−ψ) rises.
Data: Idealista, Spain’s largest online real estate platform, provides monthly listings for all nonresidential structures (retail, office, and industrial space) listed for sale from 2005 to 2018 — approximately 8.9 million property-month observations from over 1.15 million distinct capital units. The average listed price per square foot is $162 (2017 dollars); the average duration on the market is 10.5 months; each listing receives on average 800 views, 45 clicks, and 3 emails per month from prospective buyers.
Empirical facts (Section 4): Two cross-sectional regularities confirm the model’s predictions:
- Predicted price (from a hedonic regression on observable characteristics) is negatively correlated with duration — units with better observable characteristics sell faster, consistent with full-information competitive search (higher buyer valuation → higher matching rate)
- Residual price (orthogonal to observables) is positively correlated with duration — estimated slope coefficient ŷq ≈ 0.148 — consistent with asymmetric-information signaling (high-quality capital sellers post high residual prices to separate from low-quality sellers, accepting lower trading probabilities)
- The residual-price/duration slope exhibits strong countercyclical variation, roughly doubling during the Euro crisis (peak slope ≈ 0.38, compared to baseline ≈ 0.148), consistent with asymmetric information worsening during downturns
Calibration (monthly frequency, Table 4 fixed; Table 5 fitted):
- Fixed parameters: β = 0.9966 (annual rate of time preference 4%), α = 0.35 (capital share), δ = 0.0074/month (8.5% annual nonresidential depreciation), γ = 1.004 (1.6% annual TFP growth), γn = 1.0027 (1% annual population growth), ϕ = 0.0027 (3.2% annual firm exit rate), η = 0.8 (matching curvature), φ = 0.5 (seller bargaining power)
- Fitted to four data moments (slope ŷq, SD of predicted prices, SD of residual prices, mean duration): ψ = 0.9795 (probability a lemon goes unnoticed = 2% per inspection); σω = 0.72 (SD observed quality); σa = 0.58 (SD unobserved quality); m̄ = 0.267 (matching efficiency)
- Model-simulated moments match targets essentially exactly (Table 5); untargeted relationship between duration and predicted prices is also well-matched (Table 6)
Steady-state output effects (Table 7, relative to full-information benchmark):
- Total output: −1.22% in baseline (ψ = 0.9795)
- Effective capital input: −2.55% (main driver of output loss)
- Capital stock: −1.12% (32% of output effect — reduced returns to producing new capital)
- Capital unemployment rate: +1.0 pp above full-information rate of 5% (25% contribution — high-quality capital remains listed longer)
- Allocation channel: 16% contribution — information asymmetries disproportionately reduce trading of high-quality capital, lowering average quality of employed capital
- Labor input: −0.5% (26% contribution — reduced capital input lowers labor demand)
- Moving to full information (ψ → 1): output gain of +1.5% — modest at baseline, indicating the baseline economy is not far from full information
- Moving to Euro-crisis level (ψ = 0.96): output decline of ~2% — large response because the economy’s output elasticity to ψ is high
Crisis experiment (Section 5.3): An unexpected 2 percentage-point decline in ψ (to 0.96, calibrated to match the observed increase in the residual-price/duration slope during the Euro crisis), lasting 3 years and reverting with persistence ρψ = 0.94:
- Output contraction on impact: 2%
- Time to recover half the output decline: more than 5 years (slow recovery driven by persistent capital underinvestment)
- Primary mechanism: lower inspection accuracy → high-quality capital sellers reduce trading probability to signal quality → capital unemployment rate rises (especially for high-quality units) → expected return to producing new capital falls → investment contracts → capital input declines persistently
- Secondary interaction: at higher steady-state asymmetric information (ψ = 0.96), other shocks (TFP, exit rate, discount factor) are amplified — e.g., the cumulative output response to an exit rate shock is 26% larger than in a full-information economy
Scope conditions: The model abstracts from aggregate uncertainty (the baseline is steady-state analysis), financial intermediaries, and endogenous information technology. The dataset covers Spain’s nonresidential real estate market 2005–2018; the measurement of ψ from listed prices and duration assumes that residual prices fully reflect unobserved capital quality (Proposition 5’s small-search-cost approximation). The quantitative results are robust to alternative bargaining protocols (TIOLI), higher firm exit rates, inelastic labor supply, and narrower observable-characteristic sets.
Summary of a forthcoming paper, AI-assisted and human-reviewed. See the linked original for the authoritative claims and full conditions.
Q1. Why does asymmetric information generate a positive correlation between residual prices and duration?
In the model’s separating equilibrium, sellers of high-quality capital choose prices and targeting strategies that prevent low-quality sellers from mimicking them; since low-quality sellers have a lower marginal cost of accepting lower trading probabilities (their capital is worth less to them in continued use), high-quality sellers can separate by listing at higher residual prices paired with lower market tightness and lower matching rates. The correlation between residual price and duration is therefore a direct measure of the degree of asymmetric information: the slope coefficient ŷq increases monotonically as ψ decreases (Proposition 5 and Figure 4), allowing the researcher to back out ψ from the micro data.
Q2. Why is the residual-price/duration slope countercyclical?
The data show that the slope roughly doubled during Spain’s 2008–2013 downturn and euro crisis, consistent with the model’s prediction that asymmetric information (1−ψ) worsens during economic contractions. The paper interprets this as evidence that buyers’ ability to evaluate capital quality deteriorates when economic uncertainty rises — for example, during crises it is harder to assess the profitability of retail or office space based on observable characteristics alone. This countercyclical pattern motivates the crisis experiment in Section 5.3, where a 2pp increase in 1−ψ (the degree of information asymmetry) replicates the observed slope dynamics.
Q3. Why is the 2% crisis output contraction slow to recover?
The sluggishness of recovery operates through the investment channel: when high-quality capital sellers reduce trading probabilities to signal their type, they slow the transfer of used capital from sellers (firms that exit) to buyers (firms that expand), reducing the effective capital input; this lower capital input reduces the expected marginal return to producing new capital, depressing investment; because capital accumulates gradually, the output recovery inherits the slow pace of investment recovery. The persistence parameter ρψ = 0.94 (monthly) adds further sluggishness from the slow normalization of the information environment itself.
Q4. Why are the steady-state output losses modest while the crisis response is large?
The economy features a moderate baseline degree of asymmetric information (ψ = 0.9795 — only 2% lemon-detection failure), so the steady-state distortion is small (−1.22% output relative to full information); however, the economy has a large elasticity of output to ψ, so even a small deterioration in information quality (2pp) generates large output effects (−2%). This high sensitivity arises because the effects of asymmetric information are highly nonlinear: at low levels of information frictions, small increases in the lemon probability generate proportionally large increases in the required signaling by high-quality sellers, sharply reducing their trading probabilities.
Q5. How does asymmetric information interact with other shocks?
At the baseline degree of asymmetric information (ψ = 0.9795), the aggregate responses to standard shocks (TFP, discount factor, exit rate) are similar to an economy with full information; however, at the Euro-crisis level (ψ = 0.96), the cumulative output response to an exit rate shock is 26% larger than under full information. The mechanism is that asymmetric information taxes the reallocation of capital: when more capital must be reallocated (due to higher firm exit), more of it passes through the illiquid, distorted lemon market, amplifying the output effect of the underlying shock.
Q6. What policies can reduce the distortions from asymmetric information?
The paper notes two broad policy directions: (1) policies that improve information transparency — making previously private capital characteristics public, e.g., mandatory disclosure or standardized quality certification — directly raise ψ and shift the economy toward full information, eliminating the signaling distortion; (2) policies that reduce the incentive for mimicking — for example, by allowing post-transaction renegotiation after quality is revealed (the TIOLI bargaining extension in Table 8) — have similar quantitative effects to the baseline. The paper leaves the welfare analysis of specific information-provision policies for future research.
Q7. What is the role of the data in identifying the model parameters?
The four targeted moments — slope of duration on residual prices, standard deviation of predicted prices, standard deviation of residual prices, and mean duration — jointly identify the four structural parameters {ψ, σω, σa, m̄} (Proposition 5); the key insight is that ψ and m̄ are separately identified because ŷq and mean duration respond differently to each: ψ and m̄ both affect ŷq positively, but m̄ reduces mean duration while ψ increases it, providing orthogonal variation. The calibration achieves an essentially exact match of the four targeted moments (Table 5) and also matches the untargeted negative slope between duration and predicted prices (Table 6), providing an overidentification check.
Key concepts
lemon market : a secondary market for heterogeneous assets in which sellers have private information about quality; following Akerlof (1970), lemons (low-quality assets) crowd out high-quality assets unless high-quality sellers can credibly signal their type; in the paper, signaling takes the form of higher listed prices paired with lower trading probabilities.
residual price : the component of a capital unit’s listed price orthogonal to its observable characteristics (the residual from a hedonic regression); the paper’s key empirical variable, theoretically shown to be positively correlated with unobserved capital quality and with duration under asymmetric information.
inspection technology : a buyer’s technology that reveals the true quality of a capital unit with probability ψ before (or after) purchase; the accuracy ψ governs the degree of asymmetric information in the economy — lower ψ implies worse information, requiring more costly signaling by high-quality sellers.
countercyclical asymmetric information : the empirical finding that the slope between residual prices and duration roughly doubles during the Euro crisis, interpreted as deterioration in buyers’ ability to evaluate capital quality during economic downturns; motivates the crisis experiment.
three channels of output loss : the three mechanisms through which asymmetric information reduces output: (i) lower capital stock (reduced investment incentives); (ii) higher capital unemployment rate (high-quality capital remains listed longer); (iii) adverse allocation effect (high-quality capital trades less frequently, lowering average quality of employed capital).