In the published paper Futures contracts in water leasing: an experimental analysis using basin characteristics of...
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In the published paper "Futures contracts in water leasing: an experimental analysis using basin characteristics of the Rio Grande, NM" the following regression equation outputs were estimated to predict the price per acre foot of a water right: Table 3: OLS Regression Results to Predict the Price per Acre-Foot for a Temporary Water Right Explanatory Variable Estimate Quantity Traded S.E. 0.119 -1.95*** Dry Surprise 1.46*** 0.088 Wet Surprise 1.75*** 0.116 Trading Month -0.21*** 0.027 Trading Year -0.15*** 0.031 1 Month Futures -0.75*** 0.132 2 Month Futures -0.94*** 0.173 3 Month Futures -1.33*** 0.389 Next Growing Season -0.32 0.199 Across Growing Season 0.38*** 0.116 Offer to Lease Cash Crop/Capital Crop 0.52** 0.226 Cash Crop/Cash Crop 0.58*** 0.186 Cash Crop/Env. 0.10 0.245 Cash Crop/Capital Crop 0.90*** 0.221 Cash Crop/Urban 1.51*** 0.445 Cash Crop/Env. 1.00*** 0.215 Capital Crop/Cash Crop 0.23 0.191 Cash Crop/Urban 0.90*** 0.189 Capital Crop/Capital Crop 1.12*** 0.343 Capital Crop/Cash Crop 0.60*** 0.206 Capital Crop/Env. 1.12*** 0.395 Capital Crop/ Capital Crop 0.91*** 0.242 -0.39 0.403 Capital Crop/Urban Env./Cash Crop Capital Crop/Env. 1.13*** 0.352 2.25*** 0.391 Capital Crop/Urban 0.45** 0.209 Env./Capital Crop -0.17*** 0.303 Env./Cash Crop 0.79**** 0.249 Env./Urban -0.79*** 0.252 Env./Capital Crop 0.82*** 0.259 Urban/Cash Crop 1.20*** 0.178 Env./Urban 1.10*** 0.286 Urban/Capital Crop 2.13*** 0.219 Urban/Cash Crop 0.45*** 0.175 Urban/Env. 0.71" 0.277 Urban/Capital Crop 0.48* 0.275 Constant 4.50*** 0.240 Urban/Env. -0.02 0.259 Adjusted R2 0.191 F-statistic 43.09 ***.**.* denotes statistically significant at the 1%, 5% and 10% levels respectively a robust standard errors 1. Assess the predictability of this model. Is it a good model or not, explain in detail why, you should use multiple statistical inference techniques. 2. What does the term quantity with its estimated coefficient tell you about the price? Does this make sense? 3. What do the terms 1 month 2 month and 3 month futures tell you about the price considering that the omitted variable here is the spot market? Do these three variables make sense in relation to the spot market price? 4. One of the main issues with regression is multicollinearity. A variance inflation factor was calculated for each of the variables and produced the following results for a few of the variables: Bid to Lease In the published paper "Futures contracts in water leasing: an experimental analysis using basin characteristics of the Rio Grande, NM" the following regression equation outputs were estimated to predict the price per acre foot of a water right: Table 3: OLS Regression Results to Predict the Price per Acre-Foot for a Temporary Water Right Explanatory Variable Estimate Quantity Traded S.E. 0.119 -1.95*** Dry Surprise 1.46*** 0.088 Wet Surprise 1.75*** 0.116 Trading Month -0.21*** 0.027 Trading Year -0.15*** 0.031 1 Month Futures -0.75*** 0.132 2 Month Futures -0.94*** 0.173 3 Month Futures -1.33*** 0.389 Next Growing Season -0.32 0.199 Across Growing Season 0.38*** 0.116 Offer to Lease Cash Crop/Capital Crop 0.52** 0.226 Cash Crop/Cash Crop 0.58*** 0.186 Cash Crop/Env. 0.10 0.245 Cash Crop/Capital Crop 0.90*** 0.221 Cash Crop/Urban 1.51*** 0.445 Cash Crop/Env. 1.00*** 0.215 Capital Crop/Cash Crop 0.23 0.191 Cash Crop/Urban 0.90*** 0.189 Capital Crop/Capital Crop 1.12*** 0.343 Capital Crop/Cash Crop 0.60*** 0.206 Capital Crop/Env. 1.12*** 0.395 Capital Crop/ Capital Crop 0.91*** 0.242 -0.39 0.403 Capital Crop/Urban Env./Cash Crop Capital Crop/Env. 1.13*** 0.352 2.25*** 0.391 Capital Crop/Urban 0.45** 0.209 Env./Capital Crop -0.17*** 0.303 Env./Cash Crop 0.79**** 0.249 Env./Urban -0.79*** 0.252 Env./Capital Crop 0.82*** 0.259 Urban/Cash Crop 1.20*** 0.178 Env./Urban 1.10*** 0.286 Urban/Capital Crop 2.13*** 0.219 Urban/Cash Crop 0.45*** 0.175 Urban/Env. 0.71" 0.277 Urban/Capital Crop 0.48* 0.275 Constant 4.50*** 0.240 Urban/Env. -0.02 0.259 Adjusted R2 0.191 F-statistic 43.09 ***.**.* denotes statistically significant at the 1%, 5% and 10% levels respectively a robust standard errors 1. Assess the predictability of this model. Is it a good model or not, explain in detail why, you should use multiple statistical inference techniques. 2. What does the term quantity with its estimated coefficient tell you about the price? Does this make sense? 3. What do the terms 1 month 2 month and 3 month futures tell you about the price considering that the omitted variable here is the spot market? Do these three variables make sense in relation to the spot market price? 4. One of the main issues with regression is multicollinearity. A variance inflation factor was calculated for each of the variables and produced the following results for a few of the variables: Bid to Lease
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1 The table illustrates a trendline that is clearly either negatively or positively sloped Therefore following the trends one could reasonably predict the approximate quantity sold However the degree ... View the full answer
Related Book For
Essentials of Statistics for Business and Economics
ISBN: 978-1305081598
7th edition
Authors: David Anderson, Thomas Williams, Dennis Sweeney, Jeffrey Cam
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