The estimated total economic impact of a statewide hailsuppression program in the ten-year study period ranged from$68 million to $161 million, with a ten-year annual averageof $97.8 million in total economic impacts. Only six cropswere considered in this study: wheat, barley, oats, corn(grain), sunflowers, and flax. Benefits for other crops,including forage, are not included.

Agricultural Economics Report No. 247

Economic Benefitsof Crop-Hail

Reduction Effortsin North Dakota

Jerome E. JohnsonRandal C. Coon

andJohn W. Enz

Department of Agricultural EconomicsNorth Dakota State University ofAgriculture and Applied ScienceFargo, North Dakota 58105·5636

April 1989

Acknow1edgements

This study was funded in part by the North Dakota AtmosphericResource Board's Research and Evaluation Program. Mr. Bruce A. Boe,Director of the Board, was very helpful in the conceptualization andconduct of this study. He provided the copy of the CHIAA tape thatincluded the hail data used in this analysis.

The Crop-Hail Insurance Actuarial Association (CHIAA) gatheredand prepared the crop-hail insurance data processed to prepare thisanalysis. They also provided telephone assistance in interpretingsome of the coding used. Their assistance is much appreciated and wasimportant to this report.

Processing of CHIAA data required extensive and precise computerprogramming and debugging by the second author.

The CHIAA data were computed and summarized by years and countiesusing the amount of liability ($ crop value insured), amount ofpremium ($ charged for insurance), amount of loss in dollars, and theloss-cost ratio as a percent of dollars loss divided by dollarsliability and multiplied by 100. The loss-cost ratio was computed forsix crops individually and combined by counties and years.

The detailed crop production data are from the North Dakota TaxAssessment Model which the Agricultural Economics Department conductsfor the State of North Dakota. The National Agricultural StatisticalService collected and prepared the data which it pUblishes jointlywith North Dakota State University.

The authors appreciate the assistance of Mr. Larry Stearns, agraduate student in Agricultural Economics, who explored gross cropreturns per acre of treated and non-treated counties using theStatistical Analysis System on the North Dakota State Universitymainframe computer.

The authors extend their appreciation to the staff of theDepartment of Agricultural Economics who reviewed the manuscript.Their insights and comments have improved this manuscript.

Highlights

Table of Contents

. " . . . . . . . . . . . . . . . . . . . . . ..... ii

(Introduction) 1

Methods of Analysis 2

An Agricultural State 5

Some Study Concepts . . . . . . . . . . . . . . . . . . . . . . .. 7

Annual Loss-Cost Ratios Show Great Variability

Ten-Year Average Annual Loss-Cost Ratios

11

12

Values of Crop Production . . . . . . . . . . . . . . . . . . . . . 15

Possible Crop Output Savable by Cloud Seeding for HailSuppression . . . . . . . . . . .

Overall Economic Impacts of Crop Output Savable by CloudSeeding . . . . . . . . . . . . . . . . . . . . . .

References

17

21

25

Highlights

North Dakota farmers and ranchers experience substantial annuallosses of farm output because of hail. The loss-cost ratio is ameasure of the total dollar losses due to hail divided by the totaldollars of insured liability multiplied by 100 for a selected timeperiod and county. Annual county loss-cost ratios vary greatly fromyear-to-year so la-year averages are used here.

A recent study concluded that crop-hail damage in the NorthDakota Cloud Modification Project target area averaged about 43.5percent less during its operational period for the six crops studied.

Estimates of crop-hail losses and crop savings with cloud seedingfor all counties are based on crop production and hail data for the1976-1985 period. These estimates require multiplying each county'sannual value of crop production by its annual loss-cost ratio to getthe expected loss and multiplying the expected loss by the 43.5percent reduction factor to estimate the crop output savable per acrewith cloud seeding. This is that portion of crop output not lost orvalue of crop production savable with cloud seeding. The 47 non­treated counties had a la-year average annual crop output savable withcloud seeding of $23 million, which averages $1.49 per acre for thesix crops used in this study.

The six treated counties already had achieved the 43.5 percentreduction in crop losses, so these calculations required adjusting toa non-seeding situation and calculating losses from that setting. Thela-year average annual crop output savable was $2.21 per acre for thesix treated counties.

A final calculation considers the total economic impacts of allcrop output savable as this saved crop output increases marketings intheir communities and across the state. The overall contribution ofthe increased marketings and increased sales of related goods andservices throughout the economy are calculated to have a totaleconomic impact of $8.15 an acre for the six treated counties.

The estimated total statewide economic impact of cloud seedingfor the study period ranged from a low of $68 million in 1976, to ahigh in 1980 of $lql million, and a la-year annual average of $97.8million in total economic impacts.

ii

Economic Benefits of Reducing Crop-Hail Losses

In North Dakota

By

Jerome E Johnson, Randal C Coon, and John W Enz

Most No:r:th Dakotans :r:ecognize and accept the g:r:eat natural variability

of the weathe:r: of thei:r: state Its mid-continental location in the lee of

the Rocky Mountains :r:esults in la:r:ge monthly, daily, and day-to-day

temperatu:r:e changes, mode:r:ate p:r:ecipitation that is ir:r:egula:r: in space

(cove:r:age) and time, generally low humidities, and nearly continuous wlnd

North Dakotans also :r:ecognize that this climatic variability greatly

influences thei:r: social and economic livelihoods. Most evident are

blizza:r:ds that lead to closings of schools, highways, and shopping

cente:r:s; cancellation of social events; t:r:affic delays, fender benders,

and inju:r:ies. Heavy spring and S\umDe:r: :r:ainfalls lodge and damage crops

and :r:unoff overflows culverts, :r:oads, and city storm sewers. Hail can

damage crops and gardens, ca:r:s and homes, and :r:esults in time lost to fix

the :r:epairables plus other costs.

Seve:r:e and extensive d:r:oughts (for example, 1988) have a majo:r: impact

on No:r:th Dakota ag:r:iculture and ag:r:ibusinesses, households, and the

state's economy. Some a:r:eas of the state experience soa.I wate:r:

deficiencies every yea:r:, c:r:eating a continuing p:r:oblem for many fa:r:me:r:s

and communities

Johnson is P:r:ofessor of Ag:r:icultural Economics and Coon is ResearchSpecialist, Department of Agricultural Economics; and Enz is AssociateProfessor of Soil Science

-rL

North Dakota is a uniquely agricultural state Sales of crops

typically produce about 55 percent of annual cash farm income in North

Dakota, with livestock contributing 23 percent and government payments

near 22 percent Pasture, range, and hay lands provide the basis for an

extensive livestock industry in south central and western North Dakota

Both crop and forage lands can be impacted by major hail events

The North Dakota Atmospheric Resource Board (NDARB) is concerned with

losses due to hail. This economic study of losses utilizes results of a

recent study funded by the Board and data available from the Crop-Hail

Insurance Actuarial Association (CHIAA) and from other sources in the

state CHIAA has been gathering data on crop-hail insurance and losses

for several decades

This study is premised on the following finding:

Smith, Biller Jr., and Bielke Jr. 1 concluded that the crop­

hail daaage in the target area of the Horth Dakota Cloud

Bodification Project averaged about 43.5 percent lower during

the operational period. The Board funded the study and Smith et

al used CHIAA data for 1976 through 1985 for the six crops that are

included here. It is called the Smith et al reduction factor

throughout this report to properly credit their work

Bethods of Analysis

Computing the economic impacts of hail and possible benefits due to

cloud seeding for each county and year required six steps: 1),

1Smith, Paul L , James R Miller, Jr .and Paul W Mielke, Jr. An Exploratory Study of Crop-HailInsurance Data for Evidence of Seeding Effects in North Dakota. Rapid City (SD): South DakotaSchool of Mines and Technology, Institute of Atmospheric Studies, June 1987,p 10.

Calculating crop-hail loss-cost ratios by counties for 10 years using the

CHlAA data set, 2) computing gross values of production for each of the

six crops used in the Smith et al study for the years 1976-1985 using the

North Dakota Tax Assessment Model data set, 3) multiplying county loss­

cost ratios times county values of crop production to measure county value

of production (crop sales) lost each year due to hail, 4) multiplying the

county value of crop production lost by the Smith et al reduction factor

(0 435) to determine crop output potentially savable through cloud

seeding for hail suppression, 5) applying multipliers to measure what the

value of CloP output savable would mean to community and state economies,

and 6) dividing findings by total acres of the six crops in each county

to provide a common per-acre base for the analysis.

The 43.5 percent reduction in crop losses is a potential savings

because of cloud seeding, but is not absolutely certain. The reduction in

crop losses due to hail treatment means more of the crop is available to

be marketed or used on the farm. We express that as "crop output savable"

for want of better terminology.

A CHlAA tape for North Dakota provided detailed data on crop-hail

insurance contracts and losses by townships, counties, and years.

Computer processing calculated hail loss ratios and the economic measures

by counties for all years 1976 to 1985. This analysis is limited to hail

losses of six crops: wheat and durum, barley, oats, flax, sunflowers, and

corn grain Results of this analysis better represent the western portion

of the state, which includes the areas in the Smith et a L. study. The

eastern farming areas have more of total land in crops, while the Valley

4

areas include the higher returns of potatoes, sugarbeets, and other crops

that were not a part of the Smith et al study

This study considers both the two treated areas and all other counties

in developing estimates of crop-hail loss-cost ratios, possible crop sales

lost due to hail, a conversion to crop output savable due to treatment,

and the overall economic impacts of treatment on the state economy. The

two treated areas consist of six target counties: South includes Bowman,

Hettinger, and Slope counties, and North has McKenzie, Mountrail, and Ward

counties

This report opens with an economic base discussion and chart to

indicate the importance of agriculture to each region of the state It

continues with definitions of terms to be used and presents loss-cost

ratios by counties and the gross crop returns for the six crops. It

applies the Smith et al. finding to the gross crop returns for each of 10

years to measure the possible orop output sayable and converts the

possible crop output savable to obtain the overall eoonomic impacts of

hail reduction to the state. The final step is to express most estimates

as 10-year averages per aore for each county.

Ellickson (1951) reported that the chance of hail is about the same

for all farms in a given locality, but the extent of damage varies with

the crops grown. Tomatoes and vine crops are easily damaged by hail and

are slow to recover Sugarbeet leaves are easily destroyed by hail but

the plants recover quickly. Crops harvested early in a season are exposed

to hailstorms for a shorter time and suffer less from hail

5

Jones (1969) found that the average United States 1055 to hail is

about 1 3 peroent of annual value of orop produotion, with the high rate

of 3 5 peroent in the Northern Plains Next highest 1055 is about 2 5

peroent of orop output in the Mountain region. Only 1 2 peroent of the

orop is damaged in the Corn Belt but total dollar loss is large beoause of

the high value of the orops grown The Lake States and the Appalaoian

regions have the next highest rate of hail loss

An Agricultural State

North Dakota depends heavily on orop and livestook produotion for a

substantial portion of its new wealth. The eoonomio base oonsists of five

major aotivities oontributing new wealth to the :regional eoonomies The

1987 figu:res are measured in inflation-adjusted 1980 dollars A

comparison of components of the 1987 eoonomic base for eight :regions of

the state economy indicates a st:rong dependence on agriculture (see

Figures 1 and 2). The eight state planning regions are shown in Figu:re 1

11..,. _. LS"'T-~ Id-.. . _.. -1l1l_

....,;....T CENTRAL__II - _.

NORTHWEST - I-'

~~·~ORTHE"8T

J;;;.C rEl!lT ~amt"'L .- --) \- - .,.r=-~

.,- -'Ol,,"111,- lilli_ r\ -,,,. - -". 11_ ~

a~""::WE8T - llo,mtI;AaT ll<1UTl£A8T

~8T "CENTRAL

-JII_ '"011,,"- " - ~U ..,_

7-- -~ .- .- • )_r

Figure 1 State Planning Regions of North Dakota

Components of Economic Base 0'

lSI Govt OUtlays • Agl- Crops ~ Agl- Livestock o Tourism ~ Energy

Southeast

Northeast

Southeast Central

Northwest

Southwest

Northwest Central

Northeast Central

Southwest Central

Regions

State _

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0Percentages

Figure 2 Composition ln 1987 of the Economlc Bases of the Eight State Plannlng Reglonsof North Dakota. (Measured in constant 1980 = 100 dollars)

7

The Northwest, Southwest, and Southwest Central regions depend heavily

on energy for their economic activities The energy earnings, even with

the lower oil prices in 1987, were large enough to provide them great

economic strength Energy accounted for 57 percent of the new wealth in

1987 in the Northwest, 40 percent in the Southwest, and 39 percent in the

Southwest Central region.

The Southwest region also relied heavily on livestock (18 percent) and

crop (17 percent) production and federal outlays (17 percent) for its

economic base activities The economic base of the Southwest Central

region (which includes the State Capitol) obtained 39 percent of its

earnings from energy, a growing 26 percent from federal government

outlays, and 15 percent from livestock.

Federal government outlays made up 49 percent of all revenues in the

Northwest Central region, which includes the large Minot Air Base These

outlays also were important in the Northeast Central (40 percent) and

Northeast regions (40 percent). Federal government outlays provided about

a third of all state revenues in 1987.

Crop production accounted for a major portion of the economic bases in

the Northwest Central (23 percent), Northeast Central (46 percent),

Northeast (43 percent), Southeast (44 percent), and Southeast Central (45

percent) regions These regions also derive a significant portion of their

economic base from federal government outlays.

Some Study Concepts

Loss-cost ratio is the total dollar losses due to hail divided by

total dollars of insured liability times 100 This ratio is calculated

8

for a selected period for a specific area (county) It is the dollars of

loss per $100 liability resulting from hail damages to an insured crop.

The ratio is based on data in the CHIAA tape by townships, crops, and

policies by years.

Weighted loss-cost ratios were computed for each county for each year

and a simple 10-year average weighted loss-cost ratio for each county was

developed. Weighting can be adjusted by including specified crops,

selected policy forms which have different deductibles, locations (given

as township factors), and time periods Annual loss-cost ratios show

great fluctuations from year to year, so averaging is necessary to obtain

representative figures,

County Values of Crop Production per acre are the yearly dollar values

of the six crops produced in each county. They were computed using annual

county data gathered and published by the National Agricultural

Statistical Service of the U S, Department of Agriculture Data for the

period 1976 to 1985 included crop acreages, yields, production by

counties, and crop prices.

Possible Crop Sales Lost due to Hail per acre is the calculated value

of crop production lost because of damage or reduced yields due to hail

storms. These losses were computed by taking the county annualyalue of

crop production for the six crops times the county loss-cost ratios year

by year.

Possible Crop output savable due to Hail Treatment start with the

above defined county crop sales lost multiplied by the Smith et al

reduction factor Smith et al found a reduction in crop hail damage of

9

435 percent, which yields the amount of crop output savable due to cloud

seeding Crop output savable would be the "first round" or direct

economic benefit of successful cloud seeding Separate equations were

used for the non-treated and the six treated counties and are explained 2n

examples below,

1) Potential annual crop output savable due to cloud

seedinq in each non treated county is defined by:

YlI.lue of crop produat.ion x COUDty Loss-cost rs t.io X 0.435

for each of the 10 years, 1976-1985 It represents the amount of annual

gross crop returns that would not have been lost if hail reduction efforts

had achieved the 43 5 percent level reported by Smith et al

An example: Ten-year averages were developed to compensate for year-

to-year variability This hypothetical calculation is given for the

untreated county of Sheridan by using the numbers reported (in Figures 4

and 3) below as follows:

10-year Average annual value of crop prod.uction = $ 75.66 I acre10-year Average annual loss-cost ratio (5.5B?) x 0.0558Crop sales lost for six crops d.ue to hail $ ~.22 I acreSJlli.th et al. red.uction factor (~3.5?) x 0.435

1o-year Average annual crop output sa.vablebecause of cloud seeding)- $ 1.84 I acre.

The gross value of crop production per acre was multiplied by the

loss-cost ratio to give an estimated crop sales lost for the six crops

because of hail Treating reduces losses by 43,5 percent, or by about

$1 84 an acre The Sheridan County 10-year average annual crop output

savable because of cloud seeding was computed at $1,85 per acre, which is

18

close to the $184 per acre obtained in the example using the simple 10-

year average numbers This is a sizable reduction in crop losses from

successful cloud seeding An average crop sales loss of $2 37 an acre

($4 22 gross hail loss, less $1 85 (43.5 percent) reduction in hail damage

due to seeding) would still occur because treating isn't successful on

every storm

2) Annual possible crop output savable due to hail

treatment for each treated county is defined by:

( Value of crop product:ion x LOSS-COBt: rat:io ]( ~djuBt:edfact:or (1.0 - 0.435). )

less

[ Value of crop product:ion x it:s Loss-cost: rat:io I

The numerator of the equation calculates total crop sales lost per

acre as in the first equation, but that must be first divided by a factor

for this is a treated county, and finally the value of crop output savable

due to treating is deducted. A treated county already has reduced losses

due to hail treatment by an estimated 43.5 percent Here the loss-cost

ratio understates the loss by the adjustment factor of (1 - 0 435)

Bowman County numbers as an example:

Using

Gross crop returns per acre for 6-crops:Loss-cost ratioCrop sales lost with treatllent (actual)Adjusting factor (1.0 - 0._35)Crop sales lost without treatJlentCrop output saved by treating ($ 5.75 - 3.25) =

$ 54.53 I acrex 0.0596$ 3.25 I acre+ 0.565

$ 5.75$ 2.50 I acre

11

Crop output sayable in this treated county is the amount that would

have been lost if there had been no treatment ($3 25/acre) adjusted for

treatment having been used ($3 25 / (1 - 0.435) = $5 75) ~ the

expected loss without treatment ($5 75 - $3 25 = $2 50 / acre) for a

smaller loss because of cloud seeding. The reduction in crop losses of

$2 50 per acre is the crop output saved attributable to seeding It is

the potential crop sales lost adjusted for the effect of treating less the

expected crop sales lost based on the observed loss-cost ratio for the

county

Overall economic impact is the total value of direct crop output

savable because of cloud seeding plus the indirect and induced changes

that result from those losses not occurring Indirect and induced changes

are those that result from the multiplier effect, or the increases in

business activity due to subsequent rounds of increased spending and

respending of the original dollars

Economic impact can be broadly defined as the resultant increase or

decrease in economic activity resulting from expansion or shrinkage of a

particular firm, industry, or sector in the area economy 2

Annual Loss-cost Ratios Show Great Variability Annual weighted loss-

cost ratios were computed for each county and are presented for 10

southwestern counties in Figure 3 to emphasize the strong annual

variability in hail losses as measured by crop-hail loss-cost ratios

Losses for each year are presented to show how greatly losses vary from

2For more information see: Coon, Randal C, F. Larry Leistritz. Thor A Hertsgaard. and Arlen GLeholm 1985 The North Dakota Input-Output Model: ATool for AnalYZingEconomic Linkages.Fargo: North Dakota State University Department of Agricultural Economics Report No 187

12

year to year The loss-cost ratios for each county are presented as

vertical bars from left to right for the years 1976 to 1985

The largest loss-cost ratio for the six crops (see Figure 3) was in

Oliver County at 33 4 in 1977, with large ratios shown for both Morton and

Golden Valley counties in 1983 Sioux County had loss-cost ratios of 26

in 1980 and 20 in 1981. Stark County had high loss-cost percentages near

21 percent in both 1977 and 1981.

Annual loss-cost ratios represent the chance anyone farmer in a given

county has of having a crop-hail loss The 10-year average would be the

chances in a county in a similar 10-year period.

Ten-year Average Annual Loss-cost Ratios Hail events vary

greatly from year to year as shown in Figure 3, so a 10-year study period

was used in the Smith et aI, study and in this study Ten-year weighted

average annual loss-cost ratios were calculated for each county for the 10

years of 1976-1985 (Figure 4). Ratios vary from the lows in Ward,

Sargent, and Richland counties to the highs in Slope and Morton counties

A band of high average 10-year loss-cost ratios enclose Golden Valley,

Slope, Stark, Hettinger, Morton, Grant, and Sioux counties An area of

medium-high ratios include Sheridan, Wells, Eddy, Foster, Kidder,

Stutsman, Barnes, LaMoure, and Ransom counties

0.0

35.0

An 30.0n

25.0 J uJ • 1976u

• 19778 nI

• 1978l

200 I I 1--1 IIilill 19790

o 1980ss

~ 1981C

150i h H j III 19820s

~ 1983t- FBI 1984'"

10.0 I u---I j II r-H- I[IJ 1985R8 - .tI0 5.05

Adams Billings Golden Valley Morton Oliver Sioux Stark

Figure 3 Annual Loss-Cost Ratios for Seven Non-Treated Count1es in Southwestern NorthDakota, With Years Presented in order of 1976 to 1985 for Each County

LV

..J>.

DivideBurke Renville Ralelts Towner Cavalier Pembtnc

Botunecu2.27

1.84fl_2.38 2.97 1.83 2.90 4.93 2.23

Williams IMe Henry lPierce

I WalshMountrail Romsey

3.65 3.26 l Ward 2.25 3.27 4.091.07 3.64 Benson

J".,-..f4.74 JNelson Grand Forks

\Me Kenzie 2.46 1. 71

2.45 -( Mclean JSheridan wells I Eddy

2.94 5.58 6.27 7.00 Griggs Steele TraillDunn ~

~Foster

Mercer 7.87 3.46 .90 2.604.372.83Golden Billings

Burle Ig h Kidder StutsmanVolley

Olive, 5.40 Barnes Cass

4.75)

3.67 7.18 6.38 5.74 2.508.32 Stork Morlon

6.26 9.07I

~Slope La Moure Ransom RichlandHeftlnger Gront Emmons Logan

9.54 6.89 8.10

T\3.36 2.94 6.09 5.58 1. 58

Bowman Adams IMe Intosh Dickey Sorgenl

5.96 6.40 ~ 2.72 2.43 1.12

Figure 41976-1985

Ten-Year Average Loss-Cost Ratios By Counties, North Dakota.period

Averages for the

15

Values of Crop Production Annual values of crop production for the

six crops of wheat and durum, barley, oats, flax, sunflowers, and corn for

grain were calculated for each of 10 years, 1976-1985, for each county

The Smith et al study did not deal with other crops or range and pasture

land nor does this study

Annual gross values of crop production for the six crops were

calculated and weighted by the number of acres in these six crops in each

county and averaged to create the 10-year average annual gross returns per

acre of those crops as presented in Fi~lre 5, The values are reported in

nominal or current dollar terms, not adjusted for inflation.

The 10-year average annual gross crop returns per acre for the six

crops studied vary from the lows in Sioux, Billings, and Emmons counties

to the highs in Richland and Traill counties

The gross returns per acre do not include the high value speciality

crops of eastern North Dakota or truck crop farms found near cities.

Specifically. neither potatoes nor sugarbeets are included

Annual gross returns or value of production for North Dakota for the

six crops ranged from a low of $1 0 billion in 1977 to a 10-year average

of $1 5 billion or about $88 43 an acre planted to the six crops

The annual gross returns for the six crops for the six treated

counties totalled in nominal dollars a low of about $82 million in 1977 to

a high of $179 million in 1982 The 10-year average annual figure was

$132,731,897, or $78 22 per acre growing these six crops.

Total gross returns for all crops averaged about $2 billion a year as

measured in nominal dollars for the 1976-85 period The low year in gross

0'

$118.22Pembina

WalshRamsey

Cavalier

$107.36Towner

$94.74Rolette

$90.11

II

$78.98

1

'---jl Me Henry

I

$80.34

176. 30 ~;.'80 \~'''"''i87. 13

lW.,d

$92.58

Mounlroil

Burke

$76.37

$70.63

Divide

Williams

Me Kenzu,

~......r

Bowman

$61.07

$54.53

r--r Slope

$67.23

$120.22

::targenl

$96.67

$104.34 1$125.52

Coss

Ransom I Richland

$100.44

Barnes

$80.63

$86.63DiCKey

La Moure

$89.09

$95.28

Stutsman

$57.12

Me Intosh

$61.29

Logon

Foster

$57.56

Kidder

$91. 00

JEmmons

JSheridan

$75.66

Burleigh

$57.23

~Oliver

$63.56

$84.38

Grant

$58.79

~

Morton

$56.30

$66.44

I ~Mercer

$60.48

Hettinger

$76.99

$56.15

Adams 1 1

Dunn

$59.68Stark

Billings

$47.38

58.38

GoldenVolley

Figure 5~ Ten-Year Average Annual Gross Returns Per Aore By Count1es for S1X Crops Usedin the Analysis. North Dakota. for 1976-1985 period

17

value of crop production for all 53 counties was $1 33 billion in 1977,

with a high of $2 56 billion in 19B1

The percentages of gross returns of the six crops to total value of

all crops were computed for each county for the 10-year period 1976-B5

(Figure 6) This ratio presents an indication of how well the results of

this study for the six crops fit the state as a whole The ratio for the

six crops to the all-crops total ranged from 50 percent in Sioux and Walsh

counties to highs of 97 percent in Cavalier and Renville counties The

six treated county ratio averaged BB percent while the other 47 counties

earned about 75 percent of their total gross crop returns from the six

crops included in this study

Possible crop output savable due to cloud seedinq This first

measure of possible economic benefits from hail treatment was calculated

by applying the annual loss-cost ratios and the Smith et al factor

estimate to the annual gross value of production of the six crops for each

county It measures annual crop output savable due to hail treatment

As described above, two equations were used: one for the six treated

counties and another for all other counties. Each year had a different

crop-hail loss-cost ratio to be applied to its annual value of crop

production of the six crops, adjusted for possible reduction because of

cloud seeding, and a lO-year average was developed for each county

For the six treated counties, the annual value of production of the

six crops is multiplied by the loss-cost ratio and then divided by (one

minus the Smith et al reduction factor). From that value is subtracted

the value of crop production, and it is multiplied by the loss-cost ratio.

CD

Divide Burke Renvrue Bottineau Rolel1e Towner covcner Pembina

92 91

f~97 93 85 92 97 55

IWilliams

lWe'd

Me HenryWalsh

Mounlrail Pierce Romsev50

75 85 92 72 84 Benson 96

~J92 Juets on Grand Forks

\Me Kenzie 92 62_, Mct.een JSheridOn Wells I Eddy 80

I 86- \

Traill52 84 89 Griggs SteeleDunn

~r \.Foster

87 83 82 5859 69

Golden Billings Burleigh Kidder StutsmanVolley Oliver Barnes cc s s

51 60 64 54 84 90 7169

Star k Morfon

69 58I

--I Slope " t.o Moure Ransom RichlandHettinger Grant Emmons Logon

75 87 64 J 66 63 80 78 65

SorgenlBowman Adams Sioux

\Me Intosh Dickey

66 72 k 50 68 73 77

Figure 6 Ten-year Average Percentage offor All Crops, By Count~es, North Dakota,

Gross Returnsfor 1976-1985

for theperiod

S~X Crops to Total Returns

19

This equation thus calculates the total expected loss in crop sales, which

is adjusted upward because there was treatment, minus the 43 5 percent

reduced loss (or crop output savable) with clcud seeding

For the non-treated counties, possible crop output savable because of

cloud seeding is the annual gross value of production of the six crops

multiplied by the loss-cost ratio for each county, then multiplied by the

Smith et al reduction factor of 0 435

Annual crop output savable represents the value of crop production

that might have been available for sale because of cloud seeding for the

1976-1985 period The 10 years of annual crop output savable for each

county were averaged, divided by the number of acres in the six crops in

each ccunty, and presented in Fi~lre 7 Assumed crop output savable per

acre because of seeding varies from lows in Steele and Sargent counties to

the highs in Adams and Slope counties

State totals of crop output savable assuming cloud seeding based on

the six crops varied from a low of $14,871,000 in 1984 to a high of

$43,732,000 in 1980, with a 10--year average of $26,547,000 for the 1976­

1985 period The 10-year statewide average crop output savable because of

hail treatment was about $1.56 per acre growing these six crops.

The 47 non-treated counties had a 10-year average annual crop output

savable assuming successful hail treatment of $23 million, which averages

$1 49 per acre growing these six crops

Total annual crop output savable fcr the six treated counties had a

low of $798,855 in 1980, a high of $8,a16,213 in 1981, and a 10-year

Ne

Divide Burke Renville aote tte Towner ccvcner PembinaBollineau

$0.69 $0.67 (-.::.83 $1.08 $0.62 $0.62 $2.18 $1.22

Williams I

l wcr d

Me HenryWalsh

Mountrail Pierce Ramsey

$1.40 $0.72 $1.07 $1. 21 $1. 75$0.73

Benson$2.23 JNelson

\~ $1.67Grand Forks

Me KenZIe $0.88 $0.77

$1.34 LJSheridOn Wells IEddy-t McLean $3.35 $2.29 \$1.85 $2.17 Griggs Steere Traill

Dunn ~ ~ Foster

$1.17 Mercer \: $2.74 $1.30 $0.41 $0.72$0.83 t,Golden Billings

Burleigh Kidder StutsmanVolley $1. 01 Oliver Barnes cc ss

$0.92 $1.17 $1.16 $2.00 $2.28 $1.30$2.28

Stork Morton

$1.30 $2.05I

~Slope La Moure Ransom RichlandHettinger Grant Emmons Logon

$5.21 $4.05~j,$1.88 $0.66 $0.68 $2.05 $2.28 $2.18

Bowman Adami Sioux Me intosh Dickey Sorgent

1$2.54 $5.30 $1. 50 ( $0.58 $0.79 $0.47-L'\

Figure 7 Ten-Year Average Annual Crop Output Savable Per Acre Because of Cloud Seed~ng.

by Counties. North Dakota. for 1976-1985 per~od

average annual figure of $3,754,411

per acre for the six treated counties

The 10-year average came to $2 21

21

Overall economic impacts of crop output savable by cloud

seeding This applies multipliers to the annual estimates of crop output

savable assuming hail treatment to measure the total economi.c impact on

the local economies at the community and state levels

Crop output savable because of cloud seeding means greater farm

marketings, with more crop flowing through the marketing channels, more

dollars earned by truckers, elevator operators, various grain handlers and

others of the trade-- meaning an extensive series of increased spending

and respendings.

The annual total economic impacts of crop sales lost were computed for

each county and divided by the number of acres in the six crops in each

county to obtain 10-year average overall economic iJDpacts per acre, which

are presented in Figure 8.

Total economic impacts of crop output savable because of cloud seeding

at the state level was found to range from a low of $68,052,000 in 1976 to

a high in 1980 of $161,158,000 and a 10-year average of $97,834,000,

For the six treated counties, the total economic impact of crop output

savable had a low of $2,945,000 in 1980 and a high of $32,487,000 in 1981

Their 10-year average annual total economic impact was $13,837,400 or

$8 15 per acre growing the six crops.

Total economic benefits of reducing hail losses in North Dakota

includes both crop output savable because of cloud seeding and the

NN

DivideBurke Towner Cuvelier Pembina \Renville 8ollineou Rorette

$2.55 $2.47 (~.04 $3.97 $2.30 $2.30 $8.04 $4.50

IWilliams

Me Hen , 1 iMounlrail l wcr dPierce Romsey walsh

$5.14 $3.94$2.64 Benson $4.47 $6.44

~.I$8.20 $2.69 $6.18 JNelson Grand Forks

\Me Kerme$3.25 $2.82

LSheridan I..,..., ) McLean Wells Eddy

$4.93 ( $12.35 r 6.82 $8.01 $8.44sie ete Trail!

Dunn ----....... -----, Griggs

FosterMercer \ $10.09 $4.79 $1.50 $2.67$4.30 $3.07 L, .- --

GOlden Billings----

VolleyBurte Ig h KIdder Stutsman

Oliver Bornes Coss$3.74 $3.41 $4.31 $4.27 $7.38 $8.41 $4.77)

$8.39 Stark Morton

$4.79 $7.54I

,--.J Slope Hertlnger La Moure Ransom RichlandGront Emmons Logon

$19.19 $14.91 $6.92 ~ $2.42 $2.49 $7.54 $8.41 $8.05

Bowman AdornsI Sioul( Me Intosh Dickey Sorgent

$9.38 $19.54 --, $5.53 \ $2.12 $2.88 $1. 73'1

Figure 8 Ten-Year Average Annual Overall Eoonom~o Impaots Per Aore Because of CloudSeeding for Six Crops, by Counties, North Dakota, for 1976-1985 period

23

subsequent increase in spending and respendings of the earnings that the

larger crop sales would have produced The economic benefits may vary

among counties, but the 10-year average annual estimates provide a

reasonable basis for evaluation of the hail suppression cloud seeding

program

Possible direct benefits in the treated six counties can be estimated

by applying the Smith et al reduction factor to the loss-cost ratio and

cropping data to produce these estimated direct crop output savables

because of cloud seeding:

Savings Crop IndicatedCounty per acre Acres Savings

Bowman $ 2 54 x 155,020 = s 393,751

Hettinger $ 4 05 x 314,750 = 1,274,738

McKenzie $ 1 34 x 198,710 = 266,271

Mountrail $ 2 23 x 328,730 = 773,068

Slope $ 5 21 x 129,280 = 673,549

Ward s o 73 x 570,440 = 416,421

The 10-year average annual savings was $3,754,411 for all six treated

counties, for an average of $2 21 per acre for the six crops used

throughout this analysis Reduced damages to pasture and range lands

should increase the indicated benefits, as would similar damage reductions

to crops other than the six upon which this study is based The $2 21 per

acre of direct crop output savable becomes a total economic impact of

$8 15 an acre for the six treated counties

25References

Changnon, S AEvaluation"Switzerland,

,1985: "Use Of Crop-Hail Data In Hail SuppressionProc . 4th WMO Sci. Conf. Wea. Modii .. Vol. II, Geneva,563-567

Coon, Randal C , F Larry Leistritz, and Thor A Hertsgaard, 1986:Composition of North Dakota's Economic Base: A Regional Analysis Fargo:North Dakota State University, North Dakota Agricultural ExperimentStation, Department of Agricultural Economics Report No 209 96 P

Ellickson, John C 1951 Hail Insurance on Growing Crops, U SDepartment of Agriculture, Bureau of Agricultural Economics, AgriculturalInformation Bulletin No 56, June 1951 29 pp

Enz, John W , Harvey G Vreugdenhil, Jerome E Johnson, and LeRoy WSohaffner, 1982 Cloud Seeding for Rainfall Inorease - What Can WeExpect in North Dakota? Fargo: North Dakota State University, NorthDakota Agricultural Experiment Station, Soil Science Research Report # 1,Leaflet.

Johnson, J E.,et aI, 1974 The Effeots of Added Rainfall During theGrowing Season in North Dakota North Dakota State University NorthDakota, North Dakota Agricultural Experiment Station 227 p

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May 27-30Data"

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Smith, Paul L , James R Miller, Jr., and Paul W Mielke, Jr, 1987: An.Exploratory Study of Crop-Hail Insurance Data for Evidence of SeedingEffects in North Dakota. Bismarck, N.D.: The Consortium for AtmosphericResources Development for: North Dakota Weather Modification Board 21p