Local Industrial Conditions and Entrepreneurship: How Much of the Spatial Distribution Can We Explain?

Why are some places more entrepreneurial than others? We use Census Bureau data to study local determinants of manufacturing startups across cities and industries. Demographics have limited explanatory power. Overall levels of local customers and suppliers are only modestly important, but new entrants seem particularly drawn to areas with many smaller suppliers, as suggested by Chinitz (1961) . Abundant workers in relevant occupations also strongly predict entry. These forces plus city and industry fixed effects explain between 60% and 80% of manufacturing entry. We use spatial distributions of natural cost advantages to address partially endogeneity concerns.     

Competitive decision making: Two and a half frames

We argue that the study of competitive decision making has been heavily influenced by the frames of reference that are adopted by researchers. The dominant economic frame and the emergent behavioral frame describe largely separate phenomena and have little overlap. Drawing from examples of learning in games and markets, we show how each of these frames falls short of capturing some interesting elements in competitive decisions. We then describe how a coevolutionary perspective may be emerging as an integrative paradigm for the study of competitive decisions.This paper was prepared for the conference, Understanding Competitive Decision Making. Comments by the participants of that conference and Paul Shoemaker are gratefully acknowledged, as are discussions with Colin Camerer, Eldar Shafir, and Sharoni Shafir.     

Snapshot samples

We consider a coverage model where an initial event that occurs at some point in time triggers an activity of random duration that leads to some subsequent event. A snapshot sample is constructed at a fixed point in chronological time either by sampling only subjects where the initial event has occurred but the subsequent event has yet to occur (active subjects), or by sampling only subjects where both the initial and subsequent events have occurred (inactive subjects). The biases inherent in snapshot sampling can be neatly characterized by the properties of two random variables: the history (defined as the time the initial event occurs as measured into the past from the chronological point of sampling), and the active time (defined as the length of time between the initial and subsequent events). Though snapshot samples are biased, recognizing the biases enables correct inferences to be drawn from snapshot-sampled data. Considering only the case where and are independent random variables, this paper presents the probability models associated with snapshot sampling, demonstrates the problems that can occur, offers procedures for overcoming these problems, and applies the methods to interesting data sets.     

Bankruptcy Decision Making

When a firm encounters financial distress, there is a significantpossibility that, at some point, the firm itself should be shutdown and its assets put to better use. But Chapter 11 and indeedall market-mimicking reorganization regimes other than a speedyauction entrust the shutdown decision to a bankruptcy judgewho lacks information and expertise, as well as the abilityto control the timing of her decisions. Understanding the costsof entrusting the shutdown decision to a bankruptcy judge iscentral to assessing any law of corporate reorganizations. Thisarticle models the shutdown decision as the exercise of a realoption. The model suggests that the shutdown decision may loomso large in the early parts of the bankruptcy case that it erasesany significant difference between Chapter 11 and many alternativemarket-mimicking regimes. All these regimes take more time thanmandatory auctions and thus increase the cost of taking theshutdown decision away from a market actor. Moreover, the realoption itself gives parties an incentive to withhold information.Only a system of mandatory auctions both limits the amount oftime the shutdown option resides with an inexpert decision makerand forces insiders to give that decision maker sufficient informationto value the option while it is in her hands.     

Risk and the Home Equity Conversion Mortgage

This article analyzes the risks involved with reverse mortgage insurance and explains the pricing model developed for the Home Equity Conversion Mortgage (HECM) demonstration. The paper demonstrates how borrower longevity, interest rates and property value changes all affect pricing, and why the HECM model focuses on property value as the primary source of uncertainty. It goes on to explain why a random walk specification was chosen to forecast property values, and how the principal limit factors, which determine cash payments to borrowers in the HECM program, are calculated.     

The Internal and External Impact of Historical Designation on Property Values

Designation of historic properties and historic districts is increasingly used as a means to revive central-city neighborhoods and to promote urban economic development. While preservation activities are thought to generate positive externalities for surrounding neighborhoods, these external effects have been difficult to quantify. Using a database of tax-appraisal records for residential properties in Abilene, Texas, this study demonstrates that there are significant, positive externalities associated with historic designation. We perform simple cost-benefit calculations and find that the internal and external benefits more than outweigh the (nonzero) costs associated with historical designation. Moreover, from the city of Abilene's perspective the property-tax incentives provided to historic reinvestment are outweighed by the added property-tax revenue created by the increased value.     

THE BANK MERGER WAVE: The Economic Causes and Social Consequences of Financial Consolidation,Gary A. Dymski. Armonk,NY: M.E. Sharpe

Review of Industrial Organization -