Public Sector Pay in Finland

This study analyses the forces determining public and private sector pay in Finland. The data used is a 7 per cent sample taken from the Finnish 2001 census. It contains information on 42 680 male workers, of which 8 759 are employed in public and 33 921 in the private sector. The study documents and describes data by education, occupation and industry. We estimate earnings equations for the whole sample as well as for four industries (construction, real estate, transportation and health) that provide an adequate mix of both public and sector workers. The results suggest that the private-public sector pay gap of about one per cent can be accounted for by differences in observable characteristics between the sectors (3.4 per cent) and lower returns from these characteristics (-2.3 per cent). However, the industry-level analysis indicates that the earnings gaps vary across industries, and are negative in some cases. These inter-industry differences in public-private gaps persist even when the usual controls are introduced. This suggests that public sector wage setters need greater local flexibility, which should result in less uniform wages within the public sector.

Indexed versus nominal government debt under inflation and price-level targeting

This paper presents a DSGE model in which long run inflation risk matters for social welfare. Optimal indexation of long-term government debt is studied under two monetary policy regimes: inflation targeting (IT) and price-level targeting (PT). Under IT, full indexation is optimal because long run inflation risk is substantial due to base-level drift, making indexed bonds a much better store of value than nominal bonds. Under PT, where long run inflation risk is largely eliminated, optimal indexation is substantially lower because nominal bonds become a better store of value relative to indexed bonds. These results are robust to the PT target horizon, imperfect credibility of PT and model calibration, but the assumption that indexation is lagged is crucial. From a policy perspective, a key finding is that accounting for optimal indexation has important welfare implications for comparisons of IT and PT.

Suppliers of Priors: A Theory of Retailing Inspired by the Market for Chinese Antiquities

Adverse selection may thwart trade between an informed seller, who knows the probability p that an item of antiquity is genuine, and an uninformed buyer, who does not know p. The buyer might not be wholly uninformed, however. Suppose he can perform a simple inspection, a test of his own: the probability that an item passes the test is g if the item is genuine, but only f < g if it is fake. Given that the buyer is no expert, his test may have little power: f may be close to g. Unfortunately, without much power, the buyer's test will not resolve the difficulty of adverse selection; gains from trade may remain unexploited. But now consider a "store", where the seller groups a number of items, perhaps all with the same quality, the same probability p of being genuine. (We show that in equilibrium the seller will choose to group items in this manner.) Now the buyer can conduct his test across a large sample, perhaps all, of a group of items in the seller's store. He can thereby assess the overall quality of these items; he can invert the aggregate of his test results to uncover the underlying p; he can form a "prior". There is thus no longer asymmetric information between seller and buyer: gains from trade can be exploited. This is our theory of retailing: by grouping items together - setting up a store - a seller is able to supply buyers with priors, as well as the items themselves. We show that the weaker the power of the buyer�s test (the closer f is to g), the greater the seller�s profit. So the seller has no incentive to assist the buyer � e.g., by performing her own tests on the items, or by cleaning them to reveal more about their true age. The paper ends with an analysis of which sellers should specialise in which qualities. We show that quality will be low in busy locations and high in expensive locations.