Econometrics of market and non-market goods

Tabatabaei, Maryam, author
Loomis, John, advisor
Koontz, Stephen, committee member
Iverson, Terrence, committee member
McCollum, Daniel, committee member
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This dissertation illustrates how different econometric methods can be applied to market and non-market goods. The first essay focuses on forecasting cheddar cheese prices by utilizing time series models from the simplest model autoregressive order 2 AR (2) model, to more complex models such as second order vector autoregressive (VAR(2)) or second order vector error correction models (VECM(2)). One-to twelve month ahead forecast horizons for cheddar cheese levels and difference models were calculated for each forecasting methods for the out of sample time period of January 1990 to December 2013. The forecasts' accuracy was diagnosed by using root mean squared error (RMSE), and Diebold-Mariano (D-M) tests and comparing the forecasted cheddar cheese prices to existing USDA National Agricultural Statistics Service (NASS) cheddar cheese prices, and Futures. The D-M test is comparable to the RMSE test for forecasting price level, AR (2) forecasting method has lower forecasted error in January and February, and VAR (2) is more accurate from March onward. VAR (2) has the lowest RMSE for forecasting price level. In the forecasting model of price differences AR (2) forecasting method results are more accurate from January to April and VAR (2) has more accurate results from May onwards, and VECM (2) were never better than simpler forecasting methods in both forecasting price levels and price differences models. In the second essay, Colorado households' non-market values for two forest management options for reducing intensity of future wildfires and associated non-market environmental effects of wildfires has been calculated. The first policy is the traditional harvesting of pine beetle killed trees and burn on-site. The second policy also involves harvesting trees but involves moving the trees offsite and converting them into biochar, thus reducing some of the environmental effects associated with burning on-site. A contingent valuation method mail survey was implemented to evaluate these two management options. The survey achieved a 47% response rate. I used a non-parametric Turnbull estimator to calculate the willingness to pay (WTP) for burn on-site and off-site biochar conversion. The calculated WTP for burn on-site and off-site biochar conversion is $411 per household, and $470, respectively. In the third essay, household's non-market values for forest management options for avoiding forest fires in Larimer County have been calculated using a different stated preference survey design. A thousand surveys were mailed that asked respondents to rank the management options (including their costs to households) from best to worst. We used rank ordered and conditional logit models to calculate the WTP for burn on-site and biochar option. The rank ordered model outperformed the conditional logit in terms of consistency with economic theory. However even the rank ordered logit had insignificant cost coefficient for the burn on site option. The annual willingness to pay (WTP) for the biochar option, in rank-ordered logit model is $508 per household.
2014 Fall.
Includes bibliographical references.
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applied econometrics
non-market valuation
forest fires management
forecasting commodity prices
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