ECONOMIES OF SCALE IN MINING – ASSESSING UPPER BOUNDS WITH SIMULATION

As part of the trend towards increasing levels of mechanisation and automation, mines are turning to the use of larger equipment in order to achieve economies of scale. Larger trucks, for example, result in fewer hauls and fewer drivers required to haul the same quantity of ore. resulting in lower production costs. This paper uses simulation to show that larger capacity trucks also have higher maintenance costs, primarily associated with lost production due to unscheduled downtime. Specific recommendations on how to estimate the scale and impact of these costs are included.     

Bank Size and Household Financial Sentiment: Surprising Evidence from University of Michigan Surveys of Consumers

We analyze comparative advantages/disadvantages of small and large banks in improving household financial sentiment. Matching University of Michigan Surveys of Consumers household sentiment data with local banking market data from 2000 to 2014, we find surprising results—large banks have significant comparative advantages in boosting such sentiment. The findings apply across demographic groups, market types, and time periods, and are robust to different measurements and econometric methods. We contribute to the literatures on bank specialness, benefits and costs of small and large banks, household sentiment, and real effects of banking. We conjecture about the drivers of the findings, and discuss policy implications.     

Informed Lending and Security Design

We examine the role of security design when lenders make inefficient accept or reject decisions after screening projects. Lenders may be either “too conservative,” in which case they reject positive‐NPV projects, or “too aggressive,” in which case they accept negative‐NPV projects. In the first case, the uniquely optimal security is debt. In the second case, it is levered equity. In equilibrium, profitable projects that are relatively likely to break even are financed with debt, while less profitable projects are financed with equity. Highly profitable projects are financed by uninformed arm's‐length lenders.     

BUYER POWER AND THE ‘WATERBED EFFECT’*

When a buyer is able to obtain lower input prices from a supplier, is it possible that other buyers will have to pay more for the same input as a result? Is this bad for consumers? We present a model that analyzes the conditions under which the asymmetric exercise of buyer power can lead to consumer detriment through raising other buyers' wholesale prices (the ‘waterbed effect’).     

How to Solve the Price Puzzle? A Meta‐Analysis

The short‐run increase in prices following an unexpected tightening of monetary policy constitutes a puzzle frequently reported in empirical studies. Yet the puzzle is easy to explain away when all published models are quantitatively reviewed. We collect and examine about 1,000 point estimates of impulse responses from 70 articles that use vector autoregressions to study monetary transmission in various countries. We find that the puzzle is created by model misspecifications: especially by the omission of commodity prices, neglect of potential output, and reliance on recursive identification. Our results also suggest that the strength of monetary policy depends on the country’s openness, phase of the economic cycle, and degree of central bank independence.     

Supply and Demand Effects of Bank Bailouts: Depositors Need Not Apply and Need Not Run

We address two key issues concerning bank bailout effects on depositor and bank behavior. The first is whether bailouts weaken or strengthen market discipline by depositors through deposit supplies. The second is if bailed-out banks decrease or increase their deposit demands. These questions can only be adequately addressed by analyzing the effects of bailouts on both deposit quantities and prices. We do so for the Troubled Asset Relief Program (TARP) bailouts. Overall, we find that demand changes empirically dominate supply changes, and suggest significantly reduced deposit demand from bailouts. In some cases, however, supply changes dominate and indicate weakened market discipline.     

Biased Auctioneers

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price-to-estimate ratios and lower buy-in rates, pointing to estimates' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers' prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.