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This study is an empirical examination of the relationship between pricing and optimal time on the market (TOM). First, estimates of optimal TOMs for our data set are generated using a linear programming model. Next, a workable measure of pricing is provided based on predicted listing prices and predicted sales prices. We are then able to measure directly the relationship between pricing and optimal TOM. The results of our analysis indicate that both overpricing and underpricing would prevent the achievement of optimal TOM and result in suboptimal sales prices.
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Stored only when both papers are in the corpus — 69 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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