Indiana’s Starving Agriculture Industry:

 

A statistical analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Amber L. Dunning

Eco 257 Quantitative Methods

Dr. Eric Dodge

December 6, 2004

Introduction:

 

            Indiana Beach, a theme park in northern Indiana, once ran an advertising campaign with the slogan, “There’s more than corn in Indiana,” referring to the state’s reputation as an agricultural assembly line.  But how true is this reputation?  It’s hard to drive anywhere in rural Indiana without noticing farm after farm be offered up for sale.  Surely the state known for basketball games and cornfields is not in the process of weeding out one of the industries upon which Indiana was built.  Throughout this paper, I will present and analyze the agricultural industry’s trends among different commodities, different counties, and compared to the United States as a whole.

            When examining the agricultural industry’s contribution to the Indiana economy since 1977, there is a staggering downward trend.  In 1977, agriculture accounted for 3.73% of the gross state product, but by 2000, the same industry only made up 1.16% of the gross state product.  This is compared to the manufacturing industry contributions to gross state product declining from 36.75% to 29.96% in the same 23 year span.  However, the service industry’s contributions to gross state products increased from 9.48 to 17.06% from 1973 to 2000.  When examining other state’s agricultural contributions during the same time period (states selected by choosing every 15th state in an ascending alphabetical listing), Alabama experienced a decline in agricultural contribution from 2.65% to 1.72%, Nevada decreased its agricultural contribution from 1.17% to 0.79%, and Tennessee agricultural contributions reduced from 2.48% to 1.02%.  When examining the Indiana agricultural economy, one interesting finding was that while the number of farms steadily decreased over time, the mean unit of commodity per farm increased.   A possible explanation for this data would be that the smaller farms are selling and leaving the market, and therefore only larger, more productive farms remain.

 

Summary of the Data:

 

            No new data was created in this study.  Instead, I used data found by the United States Department of Agriculture National Agriculture Statistics Service (also know as the USDA NASS) and the United States Department of Commerce Bureau of Economic Analysis (also known as the BEA).  Information on how to examine the raw data can be found at the end of this paper.  The data from these sites ranged from the years 1977 to 2003, however, in order to maintain congruence between analyses, many of the statistics were pulled from the years 1997 and 2002 due to the wide availability of data in these two years.  Also, in order to simplify, certain analyses examine the data of 4 counties, each representing either the minimum value, the maximum value, or the two values on either side of the median.  In order to deepen this examination, congruent analyses will present the data of 3 counties, each representing the least populated county, the most populated county, or the median populated county.  The agricultural variables are widely diverse, and as the saying goes, comparing apples to oranges, or in this case perhaps corn and wheat, can be somewhat difficult.  Therefore, each statistical analysis will be thoroughly explained as to what variables and measures the data contains as each finding is presented in order to assure that no bias was present during the completion of this project.

 

Summary Statistics:

 

            Below is a table showing the summary statistics for the number of Indiana farms per county for 1997 and 2002. The mean number of farms per county was 725.0761 with a standard deviation of 294.0248 in 1997 and 655.3913 with a standard deviation of 277.1716 in 2002.  The median number of farms per county in 1997 was 700.5 and in 2002 the median was 623.5.  The minimum number of farms per county was 207 in 1997 and 213 in 2002.  The maximum number of farms per county in 1997 was 1688 and in 2002 the maximum was 1,551.

 

Table 1. Summary Statistics, Number of Indiana Farms by County, 1997 and 2002

 

 

Number of Farms by County, 1997

Number of Farms by County, 2002

 

 

 

Mean

725.076087

655.3913043

Standard Error

30.6542072

28.89713935

Median

700.5

623.5

Mode

735

676

Standard Deviation

294.0248264

277.1716236

Sample Variance

86450.59854

76824.10893

Range

1481

1338

Minimum

207

213

Maximum

1688

1551

Count

92

92

Confidence Level(95.0%)

60.89082304

57.40062325

 

 

            Below is a table showing the summary statistics for the number of acres in Indiana farms per county for 1997 and 2002.  The mean number of acres in farms per county was 168,751.6739 with a standard deviation of 62,181.6117 in 1997 and 163,681.1957 with a standard deviation of 64,661.8291 in 2002.  The median was 178,154.5 in 1997 and 17,2528.5 in 2002.  The minimum and maximum number of acres in farms per county were 23,836 and 285,983 for 1997 and 20,390 and 300,136 for 2002, respectively.

 

 

 

 

 

 

 

 

 

 

 

 

Table 2. Summary Statistics, Total Land in Indiana Farms, 1997 and 2002

 

 

Total Land in Farms per county, 1997

Total Land in Farms per county, 2002

 

 

 

Mean

168751.6739

163681.1957

Standard Error

6482.881166

6741.461702

Median

178154.5

172528.5

Mode

#N/A

#N/A

Standard Deviation

62181.61171

64661.82909

Sample Variance

3866552835

4181152141

Range

262147

279746

Minimum

23836

20390

Maximum

285983

300136

Count

92

92

Confidence Level(95.0%)

12877.44835

13391.08687

 

            Below is a table showing the summary statistics for the acres harvested, yield per acre and average price per bushel for corn for the years 1994 to 2003.  The mean values for area harvested (in 1000 acres), yield per harvested acres (in bushels), and average price per bushel (in $) were 70,779.2 with a standard deviation of 2,437.5644, 132.07 with a standard deviation of 8.3042, and 2.299 with a standard deviation of 0.4428, respectively.

 

Table 3. Summary Statistics for Corn, 1994-2003

 

CORN:

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Average price per bushel ($)

 

 

 

 

Mean

70779.2

132.07

2.299

Standard Error

770.825543

2.626025726

0.140019443

Median

71789.5

134.1

2.29

Mode

#N/A

#N/A

#N/A

Standard Deviation

2437.564395

8.304222487

0.442780357

Sample Variance

5941720.178

68.96011111

0.196054444

Range

7461

28.7

1.42

Minimum

65210

113.5

1.82

Maximum

72671

142.2

3.24

Sum

707792

1320.7

22.99

Confidence Level(95.0%)

1743.729852

5.940487432

0.316746228

 

            Below is a table showing the summary statistics for the acres harvested, yield per acre and average price per bushel for wheat for the years 1994 to 2003.  The mean values for area harvested (in 1000 acres), yield per harvested acres (in bushels), and average price per bushel (in $) were 56,135.8 with a standard deviation of 6,180.0845, 39.65 with a standard deviation of 3.3387, and 3.312 with a standard deviation of 0.7061, respectively.

 

Table 4. Summary Statistics for Wheat, 1994-2003

 

WHEAT:

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Average price per bushel ($)

 

 

 

 

Mean

56135.8

39.65

3.312

Standard Error

1954.314309

1.055804064

0.223302485

Median

56387.5

39.85

3.365

Mode

#N/A

#N/A

#N/A

Standard Deviation

6180.08448

3.338745606

0.706144461

Sample Variance

38193444.18

11.14722222

0.49864

Range

17016

9.2

2.07

Minimum

45824

35

2.48

Maximum

62840

44.2

4.55

Count

10

10

10

Confidence Level(95.0%)

4420.969482

2.388396547

0.505145702

 

 

Looking at Gross State Product, what percentage has agriculture historically held?

 

            Indiana’s agricultural industry’s contribution to the Indiana economy since 1977 has decreased from 3.73% of the gross state product to only 1.16% of the gross state product in 2000.  This is compared to the manufacturing industry contributions to gross state product declining from 36.75% to 29.96% in the same 23 year span.  However, the service industry’s contributions to gross state products increased from 9.48 to 17.06% from 1973 to 2000.  When examining other state’s agricultural contributions during the same time period (states selected by choosing every 15th state in an ascending alphabetical listing), Alabama experienced a decline in agricultural contribution from 2.65% to 1.72%, Nevada decreased its agricultural contribution from 1.17% to 0.79%, and Tennessee agricultural contributions reduced from 2.48% to 1.02%.

            Following are two graphs depicting the percentage of gross state product contributed by agricultural products.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1.  Indiana’s Agricultural, Manufacturing, and Service Industry Contribution to Gross State Product from 1977-2001

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2. Agricultural contributions to State Gross Product for Alabama, Indiana, Nevada, and Tennessee from 1977-2001

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


How do agricultural trends vary by county and commodity? Are there similar trends amongst crops and livestock?

 

            As mentioned earlier, there will be two sets of county data presented.  The first set was chosen by identifying the minimum, maximum, and the two counties on either side of the median for the number of farms per Indiana County.  These counties are Ohio (the minimum value), Hancock and Steuben (the two median values), and LaGrange (the maximum value).  The Indiana state average will also be presented with these counties.  This group shall be referred to as the “summary statistics counties.”  The second group of counties was chosen by identifying the minimum, maximum, and median values based on population per county.  These counties are Ohio (once again, the minimum value), Putnam (the median value), and Marion (the maximum value).  The Indiana state average will also be presented with these three counties.  This group shall be referred to as the “population counties.”

            Below are figures 3 and 4 which depict the total number of farms per county for the years 1997 and 2002.  In every depicted instance, with the exception of Marion County, the number of farms per county has declined. The values below are real numbers, i.e. 1=1 farm.

 

 

 

Figure 3. Number of Farms per Indiana County, counties chosen by summary statistics for 1997 and 2002

 

 

Figure 4. Number of Farms per Indiana county, counties chosen by population for 1997 and 2002

 

 

            Below are figures 5 and 6 which depict the percentage change of the number of farms in each county between 1997 and 2002, measured in percentages.

 

Figure 5. Change in number of farms per county between 1997 and 2002 for the summary statistics counties

 

 

Figure 6. Change in number of farms per county between 1997 and 2002 for the population counties

 

 

            Since the number of farms has, on the statewide average, declined, has this effected corn and wheat production?  Measuring the production of corn and wheat based on total output by farm or by county would be misleading since the above graphs depicted the reduction in the number of farms per county.  In order to remove that issue, yet still examine any increases or decreases in production, the below tables and graphs will look at bushels per acre.  Measuring in bushels per acre allows us to look at efficiency, which is the main goal of agricultural production.  In the case of Ohio County, values for wheat bushels per acre was not available, therefore the symbol (-) was entered in place of data.

 

 

 

 

Table 5. Corn production for 1997 and 2002 measured in bushels per acre

 

 

1997

2002

Change

 

Bushels per acre

Bushels per acre

 Bushels per acre

Ohio

83.42957456

83.15544761

-0.27413

Hancock

124.2229827

114.4490414

-9.77394

Steuben

114.8544536

89.97880418

-24.8756

LaGrange

119.4093426

92.91194802

-26.4974

Ohio

83.42957456

83.15544761

-0.27413

Putnam

110.9891047

138.1650172

27.17591

Marion

117.4252254

117.2852988

-0.13993

Indiana Average

119.3509797

118.3138877

-1.03709

 

 

Figure 7. Corn production for summary statistics counties for 1997 and 2002

 

 

 

 

 

 

 

 

Figure 8. Corn production for population counties for 1997 and 2002

 

 

Table 6. Wheat production for 1997 and 2002 measured in bushels per acre

 

 

1997

2002

Change

 

Bushels per acre

Bushels per acre

  Bushels per acre

Ohio

-

-

-

Hancock

58.61162342

53.76617874

-4.84544

Steuben

50.83511825

54.1

3.264882

LaGrange

52.1945973

52.61345253

0.418855

Ohio

-

-

-

Putnam

55.15108199

46.91341705

-8.23766

Marion

53.90073529

40.16938111

-13.7314

Indiana Average

53.59396236

51.17236297

-2.4216

 

Figure 9. Wheat production for summary statistics counties for 1997 and 2002

 

 

Figure 10. Wheat production for population counties for 1997 and 2002

 

 

            After examining crop production, I decided to look at number of livestock raised per farm.  However, this data does not include a measure to remove the reduction of the number of farms from the per farm calculation.  Therefore, please note that an increase or decrease in livestock per farm may not be representative of efficiency changes, but rather shows the differences between 1997 numbers per farm and 2002 numbers per farm.  Below are tables 7 and 8 and figures 11, 12, 13 and 14 which illustrate the changes in hogs raised per farm and cattle raised per farm.  Please also note that data was not available for Ohio County or Marion County hog production in either one or both years and therefore a symbol (-) was entered in place of data.

 

Table 7. Hogs raised in 1997 and 2002, measured in hogs per farm

 

 

1997

2002

Change

 

Hogs per farm

Hogs per farm

 Hogs per farm

Ohio

-

-

-

Hancock

161.5384615

842.7727273

681.2343

Steuben

218.5757576

141.5625

-77.0133

LaGrange

244.7285714

225.6504065

-19.0782

Ohio

-

-

-

Putnam

406.3195876

839.1320755

432.8125

Marion

85.77777778

-

-

Indiana Average

576.6964312

851.1304135

274.434

 

 

 

 

 

 

 

 

Figure 11. Hogs raised in summary statistics counties for 1997 and 2002

 

 

Figure 12. Hogs raised in population counties for 1997 and 2002

 

 

 

 

Table 8. Cattle raised in 1997 and 2002, measured in hogs per farm

 

 

1997

2002

Change

 

Cattle per farm

Cattle per farm

 Cattle per farm

Ohio

20.51977401

19.91818182

-0.60159

Hancock

23.47337278

21.96212121

-1.51125

Steuben

51.22404372

61.62676056

10.40272

LaGrange

40.8331814

44.09950249

3.266321

Ohio

20.51977401

19.91818182

-0.60159

Putnam

28.99322799

26.93693694

-2.05629

Marion

21.3125

20.51351351

-0.79899

Indiana Average

39.1304818

41.72267931

2.592198

 

 

 

Figure 13. Cattle raised in summary statistics counties for 1997 and 2002

 

 

Figure 14. Cattle raised in population counties for 1997 and 2002.

 

 

What types of relationships are present between corn and wheat production versus the price paid for that commodity?

 

            The following covariance table shows the relationships between the different variables examined for corn.  There are positive relationships found between area planted and area harvested, area planted and yield per harvested acre, area planted and production, area harvested and yield per harvested acre, area harvested and production, yield per harvested acre and production, and average price per bushel and value of production.  There are negative relationships between area planted and average price per bushel, area planted and value of production, area harvested and average price per bushel, area harvested and value of production, yield per harvested acre and average price per bushel, yield per acre and value of production, production and average price per bushel, and production and value of production.

 

 

 

 

Table 9. Covariance Table for Corn variables

 

 

Area planted (1000 acres)

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Production (1000 bushels)

Average price per bushel ($)

Value of production ($1000)

Area planted (1000 acres)

6132005

 

 

 

 

 

Area harvested (1000 acres)

5337853

5347548

 

 

 

 

Yield per harvested acre (bushels)

11511.34

10238.47

62.0641

 

 

 

Production (1000 bushels)

1.46E+09

1.38E+09

5569333

5.57E+11

 

 

Average price per bushel ($)

-575.929

-486.389

-2.48543

-231118

0.176449

 

Value of production ($1000)

-1E+09

-5.4E+08

-7311097

-5.6E+11

982613.8

7.61E+12

 

            The following correlation table shows the strength of the relationships between the variables.  A strong positive relationship is signified by a value that is close to 1, such as the relationship between yield per harvested acre and production (0.947).  A strong negative relationship will have a value close to -1, such as yield per harvested acre and average price per bushel (-0.751).

 

Table 10. Correlation Table for Corn variables

 

 

Area planted (1000 acres)

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Production (1000 bushels)

Average price per bushel ($)

Value of production ($1000)

Area planted (1000 acres)

1

 

 

 

 

 

Area harvested (1000 acres)

0.9322

1

 

 

 

 

Yield per harvested acre (bushels)

0.5901

0.562

1

 

 

 

Production (1000 bushels)

0.7887

0.7972

0.947

1

 

 

Average price per bushel ($)

-0.554

-0.501

-0.751

-0.737

1

 

Value of production ($1000)

-0.149

-0.085

-0.336

-0.273

0.8482

1

 

            The following covariance table shows the relationships between the different variables examined for wheat.  There are positive relationships found between area planted and area harvested, area planted and production, area planted and average price per bushel, area planted and value of production, area harvested and production, area harvested and average price per bushel, area harvested and value of production, yield per harvested acre and production, production and value of production, and average price per bushel and value of production.  There are negative relationships between area planted and yield per harvested acre, area harvested and yield per harvested acre, yield per harvested acre and average price per bushel, yield per acre and value of production, and production and average price per bushel.

 

 

 

Table 11. Covariance Table for Wheat variables

 

 

Area planted (1000 acres)

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Production (1000 bushels)

Average price per bushel ($)

Value of production ($1000)

Area planted (1000 acres)

24676570

 

 

 

 

 

Area harvested (1000 acres)

27061024

34374100

 

 

 

 

Yield per harvested acre (bushels)

-6742.46

-2901.61

10.0325

 

 

 

Production (1000 bushels)

6.45E+08

1.13E+09

435267.7

6.61E+10

 

 

Average price per bushel ($)

2085.208

1739.138

-1.6156

-24583.1

0.448776

 

Value of production ($1000)

6.7E+09

7.5E+09

-2053276

1.64E+11

911761.3

2.58E+12

 

            In the following correlation table, the strongest positive relationship is found between area planted and area harvested (0.9292).  The strongest negative relationship is found between yield per harvested acre and average price per bushel (-0.7614).

 

Table 12. Correlation Table for Wheat variables

 

 

Area planted (1000 acres)

Area harvested (1000 acres)

Yield per harvested acre (bushels)

Production (1000 bushels)

Average price per bushel ($)

Value of production ($1000)

Area planted (1000 acres)

1

 

 

 

 

 

Area harvested (1000 acres)

0.9292

1

 

 

 

 

Yield per harvested acre (bushels)

-0.4285

-0.1562

1

 

 

 

Production (1000 bushels)

0.5048

0.7494

0.5345

1

 

 

Average price per bushel ($)

0.6266

0.4428

-0.7614

-0.143

1

 

Value of production ($1000)

0.8408

0.7966

-0.4038

0.3979

0.8479

1

 

 

 

 

 

 

 

 

Are there differences between the price paid for corn and wheat?

 

            Below is a graph showing the differences in the average prices per bushel for corn and wheat during the years 1994-2003.  It appears that wheat prices are always higher than corn prices, for the average price per bushel.

 

 

 

 

 

 

Figure 15. Comparison between corn and wheat prices between 1994-2003.

 

           

            In order to test this idea, I have set up the following null and alternative hypotheses, the null hypothesis stating that the difference between the average price per bushel for corn and wheat equals zero, or in other words, that the average price per bushel for corn and wheat are the same.  The alternative hypothesis is that there is a difference between the average price per bushel for wheat and corn. The hypotheses are listed below:

 

            Ho: (μ wheat  –  μ corn) = 0

            Ha: (μ wheat  –   μ corn) ≠ 0

           

            Since there are only 10 years (observations) in this sample, a t-test with 9 degrees of freedom must be used.  I chose a= 0.05.  With a p-value of 0.0000023772, we would not accept the null hypothesis, and conclude that there is a difference between the average price per bushel for wheat and the average price per bushel for corn.  Below are the results of the t-test:

 

 

 

 

 

 

 

 

 

Table 13. T-test results for hypothesized mean difference of 0

 

t-Test: Paired Two Sample for Means

 

 

Average Price Per Bushel

 

 

 

WHEAT

CORN

Mean

3.312

2.299

Variance

0.49864

0.196054444

Observations

10

10

Pearson Correlation

0.962124382

 

Hypothesized Mean Difference

0

 

Df

9

 

t Stat

10.50174887

 

P(T<=t) one-tail

1.1886E-06

 

t Critical one-tail

1.833113856

 

P(T<=t) two-tail

2.3772E-06

 

t Critical two-tail

2.262158887

 

 

            Figure 16 shows the bushels yielded per acre plotted against the average prices per bushel for corn and wheat between the years of 1994 and 2003.  The equation for the regression line for wheat is y = 9.6971 – 0.161 x.  The r-squared value is 0.5797 which means that 57.97% of the data can be explained by this line.  The equation for the regression line for corn is y = 7.5879 – 0.04 x.  The r-squared value is 0.5641 which means that 56.41% of the data can be explained by this line.

 

Figure 16. Relationship between bushels per acre and price per bushel for corn and wheat for 1994-2003

 

 

            Following are Tables 14 and 15, which are regression analysis tables for wheat and corn.  The average price per bushel for each commodity was chosen as the dependent variable due to the fact that it makes economic sense for price to fluctuate due to a large harvest or a poor harvest, as well as the total amount of the commodity that was harvested.  The variables are the same variables used in Tables 9-12, however, after noticing symptoms of multicollinearity, the variables related to the area planted, production, and value of production were removed in order to present a more accurate test.  For wheat, Table 14, the adjusted r-squared value is 0.5979 which means that 59.79% of the average price per bushel is explained by the area harvested and the yield per harvested acre.  For multiple independent variables, this is a very good result.  This also passes the F-test since the F-value is 0.0171 we can say this model is significant. The intercept (in literal terms) states that if there were zero acres harvested at a yield of zero bushels per harvested acre, then the average price per bushel of wheat would be $7.1331.  The coefficient for the area harvested says that for every additional 1000 acres harvested, the average price per bushel of wheat would increase $0.00003792 and for every additional bushel yielded from a harvested acre, the average price per bushel of wheat would increase -$0.1501 (or decrease by $0.1501). The intercept for the average price per bushel of wheat can be accepted at a 97.8221% confidence level.  The coefficient for the area harvested can be accepted at an 83.5161% confidence level.  The coefficient for the yield per harvested acre for wheat can be accepted at 98.7155% confidence level.

 

Table 14. Regression statistics for wheat

 

PRICE OF WHEAT

 

 

 

 

 

 

 

 

 

 

 

Regression Statistics

 

 

 

 

 

Multiple R

0.828988775

 

 

 

 

R Square

0.68722239

 

 

 

 

Adjusted R Square

0.597857358

 

 

 

 

Standard Error

0.447799516

 

 

 

 

Observations

10

 

 

 

 

 

 

 

 

 

 

ANOVA

 

 

 

 

 

 

df

SS

MS

F

Significance F

Regression

2

3.084089152

1.542044576

7.690059283

0.017112947

Residual

7

1.403670848

0.200524407

 

 

Total

9

4.48776

 

 

 

 

 

 

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

 

Intercept

7.133117798

2.427988386

2.937871466

0.021779068

 

Area harvested (1000 acres)

3.79269E-05

2.44532E-05

1.550999404

0.164838919

 

Yield per harvested acre (bushels)

-0.150067388

0.045263303

-3.315431688

0.012845348

 

 

 

            For corn, in Table 15 below, the adjusted r-squared value is 0.4512 which means that 45.12% of the average price per bushel is explained by the area harvested and the yield per harvested acre.  For multiple independent variables, this is a good result.  This also passes the F-test since the F-value is 0.0508 we can say this model is significant. The intercept (in literal terms) states that if there were zero acres harvested at a yield of zero bushels per harvested acre, then the average price per bushel of corn would be $8.6107.  The coefficient for the area harvested says that for every additional 1000 acres harvested, the average price per bushel of corn would increase -$0.00002088 (or decrease by $0.00002088) and for every additional bushel yielded from a harvested acre, the average price per bushel of corn would increase -$0.0366 (or decrease by $0.0366). The intercept for the average price per bushel of wheat can be accepted at a 96.9809% confidence level.  The coefficient for the area harvested can be accepted at a 28.8292% confidence level.  The coefficient for the yield per harvested acre for wheat can be accepted at 94.4951% confidence level.

 

Table 15. Regression statistics for corn

 

PRICE OF CORN

 

 

 

 

 

 

 

 

 

 

 

Regression Statistics

 

 

 

 

 

Multiple R

0.757046918

 

 

 

 

R Square

0.573120037

 

 

 

 

Adjusted R Square

0.451154333

 

 

 

 

Standard Error

0.328029926

 

 

 

 

Observations

10

 

 

 

 

 

 

 

 

 

 

ANOVA

 

 

 

 

 

 

df

SS

MS

F

Significance F

Regression

2

1.011264574

0.50563229

4.6990262

0.050824159

Residual

7

0.753225426

0.10760363

 

 

Total

9

1.76449

 

 

 

 

 

 

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

 

Intercept

8.61067862

3.177152936

2.71018701

0.0301908

 

Area harvested (1000 acres)

-2.08764E-05

5.42324E-05

-0.3849433

0.7117083

 

Yield per harvested acre (bushels)

-0.036602281

0.015919012

-2.2992809

0.0550494

 

 

Conclusions

 

            From this project, we can conclude that the average number of farms per county has decreased from 1997 to 2002.  We can also conclude that the contribution of the agriculture industry to the Indiana economy has decreased from 1977 to 2000.  Our hypothesis test allowed us to conclude that there is a difference between the average price per bushel of wheat and the average price per bushel of corn.  In a further project, I would collect data on the cost of inputs for both corn and wheat to be able to determine which crop is more profitable to farms.  Also, data collected on the price paid per pound of the livestock commodities would allow a hypothesis test to be set up to see if there is a difference in prices between livestock and crops.  We can also conclude from the ANOVA tables that when farmers increase the yield per harvested acre for corn or wheat, this causes a decrease in the average price paid per bushel, which in a way punishes farmers for being efficient.  Further testing could search for a variable that may explain this finding.