In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103 1977 1,295,000 1,295,000 2,125 2,749,000 98 1978 1,376,000 1,376,000 2,055 2,831,000 133 1979 1,214,000 1,214,000 1,680 2,041,000 170 1980 1,336,000 1,336,000 1,425 1,905,000 203 1981 1,577,900 1,577,900 2,110 3,326,000 174 1982 1,619,100 1,619,100 2,290 3,701,000 165 1983 1,861,200 1,861,200 1,830 3,410,100 174 1984 1,801,200 1,801,200 2,080 3,742,300 172 1985 1,962,500 1,962,500 2,660 5,226,000 156 1986 1,999,100 1,995,100 2,200 4,458,300 121 1987 1,964,700 1,962,700 2,000 3,946,000 108 1988 1,938,400 1,934,400 1,200 2,381,500 141 1989 2,144,800 2,134,700 2,000 4,172,200 167 1990 2,209,600 2,205,500 2,700 5,884,400 140 1991 2,175,084 2,173,054 2,200 4,806,300 115 1992 2,173,000 2,084,100 2,800 5,807,700 121 1993 2,077,200 1,983,000 1,800 3,637,300 123 1994 1,661,200 1,657,200 2,200 3,696,600 139 1995 1,626,700 1,614,500 2,100 3,404,700 193 1996 1,709,700 1,699,600 2,600 4,376,500 210 1997 1,574,200 1,570,200 2,100 3,350,200 184 1998 1,313,200 1,307,100 2,500 3,219,700 178 1999 1,288,800 1,272,700 2,500 3,158,300 164 2000 1,588,300 1,572,100 2,700 4,266,000 152 2001 1,598,400 1,582,200 2,200 3,430,600 162 2002 1,375,800 1,361,700 2,400 3,325,200 180 2003 1,361,800 1,339,500 2,900 3,944,800 177 2004 1,276,600 1,220,000 3,000 3,707,300 162 2005 1,149,300 1,092,700 2,200 2,367,600 139 2006 1,331,500 1,323,300 2,900 3,794,900 154 2007 1,195,800 1,173,500 2,700 3,211,400 244 2008 1,331,500 1,289,000 3,300 4,280,900 293 2009 1,333,400 1,246,400 3,300 4,144,900 225 2010 1,230,200 1,175,600 2,800 3,250,900 212 2011 897,200 860,000 2,600 2,228,900 275 2012 1,222,000 1,205,800 3,300 3,923,000 276 2013 1,425,400 1,348,300 3,800 5,160,000 270 2014 1,246,400 1,167,500 3,300 3,797,500 217 2015 1,282,800 1,252,400 3,400 4,218,300 225 2016 1,210,500 1,192,700 3,500 4,217,400 229 2017 1,119,100 1,085,400 3,299 4,475,900 249 2018 1,186,600 1,169,100 4,099 4,791,600 251 2019 1,280,300 1,235,400 4,088 4,969,400 235 2020 1,282,610 1,278,361 4,126 5,274,100 236 2021 1,174,519 1,164,118 3,222 3,750,909 351 2022 1,252,259 1,218,670 3,905 4,758,248 436 (d) Find the expected price for wheat for this crop year, then predict how much wheat will be seeded in Manitoba in 2023 year based upon this price. Based upon recent trends in Manitoba, justify why you do or do not think this is a reasonable prediction. e) Using the Jarque-Bera test, determine whether the data series used in this question are normally distributed. Show all your work, and be sure to do all parts of the hypothesis test. (f) Re-estimate your model, using only the last 30 years of data. How do your results change? Why do you think this is, and what does it tell you about the robustness of your model? (g) Re-estimate your model, using only the last 30 years of data, using a log-log functional form. Fully interpret your results, especially the interpretation of your new slope parameter. (h) What other variables do you think could/should be added to this model to make it better? Write out your expanded model in econometric notation. Carefully describe why any variables you add would improve the model. Ensure any variables you add keep the model consistent with Koutsoyiannis’ desirable properties of any econometric model.

In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103 1977 1,295,000 1,295,000 2,125 2,749,000 98 1978 1,376,000 1,376,000 2,055 2,831,000 133 1979 1,214,000 1,214,000 1,680 2,041,000 170 1980 1,336,000 1,336,000 1,425 1,905,000 203 1981 1,577,900 1,577,900 2,110 3,326,000 174 1982 1,619,100 1,619,100 2,290 3,701,000 165 1983 1,861,200 1,861,200 1,830 3,410,100 174 1984 1,801,200 1,801,200 2,080 3,742,300 172 1985 1,962,500 1,962,500 2,660 5,226,000 156 1986 1,999,100 1,995,100 2,200 4,458,300 121 1987 1,964,700 1,962,700 2,000 3,946,000 108 1988 1,938,400 1,934,400 1,200 2,381,500 141 1989 2,144,800 2,134,700 2,000 4,172,200 167 1990 2,209,600 2,205,500 2,700 5,884,400 140 1991 2,175,084 2,173,054 2,200 4,806,300 115 1992 2,173,000 2,084,100 2,800 5,807,700 121 1993 2,077,200 1,983,000 1,800 3,637,300 123 1994 1,661,200 1,657,200 2,200 3,696,600 139 1995 1,626,700 1,614,500 2,100 3,404,700 193 1996 1,709,700 1,699,600 2,600 4,376,500 210 1997 1,574,200 1,570,200 2,100 3,350,200 184 1998 1,313,200 1,307,100 2,500 3,219,700 178 1999 1,288,800 1,272,700 2,500 3,158,300 164 2000 1,588,300 1,572,100 2,700 4,266,000 152 2001 1,598,400 1,582,200 2,200 3,430,600 162 2002 1,375,800 1,361,700 2,400 3,325,200 180 2003 1,361,800 1,339,500 2,900 3,944,800 177 2004 1,276,600 1,220,000 3,000 3,707,300 162 2005 1,149,300 1,092,700 2,200 2,367,600 139 2006 1,331,500 1,323,300 2,900 3,794,900 154 2007 1,195,800 1,173,500 2,700 3,211,400 244 2008 1,331,500 1,289,000 3,300 4,280,900 293 2009 1,333,400 1,246,400 3,300 4,144,900 225 2010 1,230,200 1,175,600 2,800 3,250,900 212 2011 897,200 860,000 2,600 2,228,900 275 2012 1,222,000 1,205,800 3,300 3,923,000 276 2013 1,425,400 1,348,300 3,800 5,160,000 270 2014 1,246,400 1,167,500 3,300 3,797,500 217 2015 1,282,800 1,252,400 3,400 4,218,300 225 2016 1,210,500 1,192,700 3,500 4,217,400 229 2017 1,119,100 1,085,400 3,299 4,475,900 249 2018 1,186,600 1,169,100 4,099 4,791,600 251 2019 1,280,300 1,235,400 4,088 4,969,400 235 2020 1,282,610 1,278,361 4,126 5,274,100 236 2021 1,174,519 1,164,118 3,222 3,750,909 351 2022 1,252,259 1,218,670 3,905 4,758,248 436 (d) Find the expected price for wheat for this crop year, then predict how much wheat will be seeded in Manitoba in 2023 year based upon this price. Based upon recent trends in Manitoba, justify why you do or do not think this is a reasonable prediction. e) Using the Jarque-Bera test, determine whether the data series used in this question are normally distributed. Show all your work, and be sure to do all parts of the hypothesis test. (f) Re-estimate your model, using only the last 30 years of data. How do your results change? Why do you think this is, and what does it tell you about the robustness of your model? (g) Re-estimate your model, using only the last 30 years of data, using a log-log functional form. Fully interpret your results, especially the interpretation of your new slope parameter. (h) What other variables do you think could/should be added to this model to make it better? Write out your expanded model in econometric notation. Carefully describe why any variables you add would improve the model. Ensure any variables you add keep the model consistent with Koutsoyiannis’ desirable properties of any econometric model.

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity.

Year	Seeded Area (hectares)	Harvested Area (hectares)	Average Yield (kg per ha)	Production (tonnes)	Price per Tonne ($/tonne)
1966	1,317,000	1,317,000	1,630	2,150,000	65
1967	1,424,000	1,424,000	1,720	2,449,000	60
1968	1,376,000	1,376,000	1,800	2,477,000	48
1969	1,012,000	1,012,000	1,720	1,742,000	46
1970	567,000	567,000	1,465	830,000	52
1971	1,019,000	1,019,000	1,975	2,014,000	50
1972	1,052,000	1,052,000	1,785	1,878,000	68
1973	1,214,000	1,214,000	1,725	2,095,000	158
1974	1,133,000	1,133,000	1,415	1,605,000	147
1975	1,255,000	1,255,000	1,690	2,123,000	130
1976	1,538,000	1,538,000	1,820	2,803,000	103
1977	1,295,000	1,295,000	2,125	2,749,000	98
1978	1,376,000	1,376,000	2,055	2,831,000	133
1979	1,214,000	1,214,000	1,680	2,041,000	170
1980	1,336,000	1,336,000	1,425	1,905,000	203
1981	1,577,900	1,577,900	2,110	3,326,000	174
1982	1,619,100	1,619,100	2,290	3,701,000	165
1983	1,861,200	1,861,200	1,830	3,410,100	174
1984	1,801,200	1,801,200	2,080	3,742,300	172
1985	1,962,500	1,962,500	2,660	5,226,000	156
1986	1,999,100	1,995,100	2,200	4,458,300	121
1987	1,964,700	1,962,700	2,000	3,946,000	108
1988	1,938,400	1,934,400	1,200	2,381,500	141
1989	2,144,800	2,134,700	2,000	4,172,200	167
1990	2,209,600	2,205,500	2,700	5,884,400	140
1991	2,175,084	2,173,054	2,200	4,806,300	115
1992	2,173,000	2,084,100	2,800	5,807,700	121
1993	2,077,200	1,983,000	1,800	3,637,300	123
1994	1,661,200	1,657,200	2,200	3,696,600	139
1995	1,626,700	1,614,500	2,100	3,404,700	193
1996	1,709,700	1,699,600	2,600	4,376,500	210
1997	1,574,200	1,570,200	2,100	3,350,200	184
1998	1,313,200	1,307,100	2,500	3,219,700	178
1999	1,288,800	1,272,700	2,500	3,158,300	164
2000	1,588,300	1,572,100	2,700	4,266,000	152
2001	1,598,400	1,582,200	2,200	3,430,600	162
2002	1,375,800	1,361,700	2,400	3,325,200	180
2003	1,361,800	1,339,500	2,900	3,944,800	177
2004	1,276,600	1,220,000	3,000	3,707,300	162
2005	1,149,300	1,092,700	2,200	2,367,600	139
2006	1,331,500	1,323,300	2,900	3,794,900	154
2007	1,195,800	1,173,500	2,700	3,211,400	244
2008	1,331,500	1,289,000	3,300	4,280,900	293
2009	1,333,400	1,246,400	3,300	4,144,900	225
2010	1,230,200	1,175,600	2,800	3,250,900	212
2011	897,200	860,000	2,600	2,228,900	275
2012	1,222,000	1,205,800	3,300	3,923,000	276
2013	1,425,400	1,348,300	3,800	5,160,000	270
2014	1,246,400	1,167,500	3,300	3,797,500	217
2015	1,282,800	1,252,400	3,400	4,218,300	225
2016	1,210,500	1,192,700	3,500	4,217,400	229
2017	1,119,100	1,085,400	3,299	4,475,900	249
2018	1,186,600	1,169,100	4,099	4,791,600	251
2019	1,280,300	1,235,400	4,088	4,969,400	235
2020	1,282,610	1,278,361	4,126	5,274,100	236
2021	1,174,519	1,164,118	3,222	3,750,909	351
2022	1,252,259	1,218,670	3,905	4,758,248	436

(d) Find the expected price for wheat for this crop year, then predict how much wheat will be seeded in Manitoba in 2023 year based upon this price. Based upon recent trends in Manitoba, justify why you do or do not think this is a reasonable prediction.

e) Using the Jarque-Bera test, determine whether the data series used in this question are normally distributed. Show all your work, and be sure to do all parts of the hypothesis test.

(f) Re-estimate your model, using only the last 30 years of data. How do your results change? Why do you think this is, and what does it tell you about the robustness of your model?

(g) Re-estimate your model, using only the last 30 years of data, using a log-log functional form. Fully interpret your results, especially the interpretation of your new slope parameter.

(h) What other variables do you think could/should be added to this model to make it better? Write out your expanded model in econometric notation. Carefully describe why any variables you add would improve the model. Ensure any variables you add keep the model consistent with Koutsoyiannis’ desirable properties of any econometric model.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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