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Analysis of data obtained from an ongoing internet search indicates that the U.S. deer harvest has been falling since about the year 2000. California has had the largest decline from peak to recent harvest of any state. Declining timber sales are highly correlated with the decline in California. States like California with a relatively high proportion of public land, a low hunter success rate, and a persistently skewed buck-to-doe harvest ratio report a lower harvest as a percent of peak. An economic framework is presented to explain how the public decision making process for deer management and the practice of setting the price of deer hunting licenses well below market equilibrium incentivizes some of these result.

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Finding data to feed into financial and risk management models can be challenging. Many analysts attribute a lack of data or quality information as a contributing factor to the worldwide financial crises that seems to have begun in the U.S. subprime mortgage market. In this paper, a new source of data, key word search statistics recently available from Google, are applied in a experiment to develop a short-term forecasting model for the number of foreclosures in the U.S. housing market. The keyword search data significantly improves forecast of foreclosures, suggesting that this data can be useful for financial risk management. More generally, the new data source shows promise for a variety of financial and market analyses.

No abstract