BSE and the US Economy

BSE and the US Economy:

Input-Output Model Perspective

Osei-Agyeman Yeboah

North Carolina Agricultural & TechnicalStateUniversity

Greensboro, NC27411

Ellene Kebede

TuskegeeUniversity

Tuskegee, AL36088

Victor Ofori-Boadu

North Carolina Agricultural & TechnicalStateUniversity

Greensboro, NC27411

Albert Allen

MississippiStateUniversity

Mississippi State, MS39762

August 2006

BSE and the US Economy:

Input-Output Model Perspective

Abstract

The potential impact of a BSE outbreak on the US economy is modeled in input-output setting using 2002 US IMPLAN data. An outbreak of BSE would hurt the US beef industry, other agriculturally-related industry, and the rest of the economy as a whole. The worse effects occur in the beefcattle and farming industries. Generally, the economyof every county would be hurtgiven the fact that cattle are produced in all the 50 states. But it is apparent that the damage would be substantial inthose regions and households which already suffer the severest economic damage.

BSE and the US Economy:

Input-Output Model Perspective

INTRODUCTION

For nearly two decades demand for US beef has been affected by bovine spongiform encephalopathy (BSE) after its potential danger to human health was exposed by (Holt and Phillips 1988); (Dealler 1993); (Sawcer 1993); and (Lacey 1993). The BSE outbreak in the UK during the mid 1990s and its possible link to cases of human Creutzfeldt-Jakob disease led various agencies of the US government to implement control measures. The spread of BSE to Japan and Canada during 2003 led to increased surveillance and research funding by the USDA. When BSE was reported in Washington the same year, stronger regulatory efforts increased production cost by $0.45 per head and proposed BSE measures would cost 5 times that for fed cattle (15 times that for non-fed cattle) according to Coffey, Mintert, Fox, Schroeder, and Valentin (2005).

It has become commonplace to say that the consequences of the BSE crisis reach far beyond the farm gate. However, quantifying the extent and significance of these secondary impacts is more problematic. Aggregate estimates of employment and value-added generated by beef farming and beef processing provide only a partial understanding that exist between beef production, other farm sectors and ancillary industries and the sector’s role in the national economy. These estimates do not capture the extent and economic importance ofinterindustry linkage. The beef industryis linked to other sectors in the economy through a network of input purchases and output sales. Changes in the level of demand for beef, both in U.S. and other markets, will have spin-ofeffects on the quantity of inter-industry sales and purchases.

In this paper, U.S. input-output(I-O) model is developed using IMPLAN 2002 economic data to capture not only the direct effects of reduction in demand for cattle industry outputdue toBSE on beef production but also wider impacts on suppliers of farm inputs, food processors, and other nonagricultural sectors. Output, income, andemployment impacts arising from reduced demand for beef are estimated. The long-run effects of BSE on the US economy would be serious in the absence of effective stabilization measures. The worse effects would take place in the beef cattle and farming industries.

A Review of BSE Industrial Impacts

In the week following the Washington BSE case in December 2003 cattle prices fell by 16% and cattle future prices 20% but they rose back during the first quarter of 2004. Had the low prices held, the cattle industry would have lost $2 billion during the first quarter of 2004(Coffey, Mintert, Fox, Schroeder, and Valentin 2005).

The consumer survey of Henderson (2003) suggests US beef demand could fall as much as 15% with a BSE outbreak. Coffey, Mintert, Fox, Schroeder, and Valentin (2005) use a regionally targeted consumer survey and find over three quarters of consumers did not change habits because of the BSE case but that subsequent cases, particularly multiple ones, could have a significant impact. Jin, Skripnitchenko, and Koo (2004) estimate there would be a 20% domestic decline of beef consumption with additional BSE outbreaks in the United States.

Within days after the 2003 Washington case 53 countries including major importers such as Japan, Mexico, South Korea, and Canada banned imports of US beef. Exports of $4 billion accounted for 10% of US beef production during 2003 and the bans reduced exports by 82%. If all exported beef were consumed domestically, the increased quantity would have lowered domestic beef prices 16% as developed by Henderson (2003).

During the second half of 2004 cattle future prices remained perhaps 10% lower than had been expected. Francl (2003) points out that based on the expected sale of over 25 billion pounds in 2004 every $10 per hundredweight drop in price results in a $2.5 billion drop in revenue. Lost exports would then account for a loss of $1 billion revenue with total lost revenue of about $3.5 billion.

From 1998 to 2002, the US exported a yearly average of $1.4 billion of beef products and Feuz (2005) estimates that exports during the period increased the price of cattle by about $40 per head. Gross receipts from sales of cattle and calves in 2000 totaled $41 million accounting for 21% of all agricultural receipts. BSE would impact other agricultural sectors and the present input-output model offers perspective on its impact on the aggregate economy as well.

A Brief Review of Literature on BSE and Consumer’s Reponses

BSE has mainly occurred in European countries and, therefore, studies of BSE outbreak and consumers’ responses have focused on Europeancases. Studies have approached the BSE case from three different directions. The first group investigatedconsumers’ responses using contingent valuation method (CVM). The second group analyzes structural changes in consumers’ preferences or producers’ profits while the third group investigates economic impacts of the outbreaks.

Among these studies is an examination by Latouche, Rainelli, and Vermersch (1998). They conducted a survey using CVM to analyze consumer behavior in the area of Rennes, France after the BSE crisis. Their survey revealed that consumers werewaiting for greater transparency and they would accept paying for it.

In regard to the issue of consumers’ preferences after the BSE outbreak, Mangen and Burell (2001) investigated a structural change in Ductch consumers’ preferences for meat and fish, following U.K. government’s announcement. They used switching Almost Ideal DemandSystem (AIDS) model and a sample period that covers January 1994 through May 1998. The hypothesis of constancy of the parameters of the AIDS model for meat and fish was rejected against a more general time-varying parameter model. The combined effects of the underlying trends and irreversible components of the BSE effects were against beef, minced beef, and meat products, in favor of pork, prepared meat, poultry and fish.

Under the third group, Ashworth and Mainland (1995) reviewed economic consequences of the BSE outbreak for the British meat industry. Adda (2002) investigated the effects of past consumption of risky goods on current consumption patterns, using the “mad cow” crisis as a natural experiment. Consumers with intermediate levels of past consumption decreased their demand for beef and sought higher quality products, while low-and high-stock consumers did not alter their behavior after crisis. Verbeke and Ward (2001) investigated fresh meat consumption in Belgium during the period from 1995 through 1998 using an AIDS model. In specifying the demand system, they incorporated a media index mainly pertaining to BSE; their results showed that television publicity has a negative impact on beef expenditure, in favor of pork. Burton and Young (1996) investigated the impact of BSE on the demand for beef and other meats in the United Kingdom. Indices of media coverage of BSE are incorporated in a dynamic AIDS model of meat demand.

In the U.S, Henderson (2003) conducted consumer surveys during the BSE outbreak in Washington, the results suggested U.S. beef demand could fall by as much as 15 percent. However, research indicated that the impact on domestic demand could be small because consumers respond differently to food safety concerns than to long-run health concerns. To investigate the potential impact of additional U.S. BSE discoveries, Coffey, Mintert, Fox, Schroeder, and Valentin(2005) used a regionally targeted consumer survey. The results suggested that most consumers (77 percent) did not change consumption habits because of the first U.S. BSE case, but that subsequent discoveries, particularly of multiple cases, could have significant impact on demand. Jin, Skripnitchenko, and Koo(2004) estimated 20 percent domestic decline in beef consumption if there are any additional BSE outbreaks in the United States.

MODEL CONSTRUCTION AND STRUCTURE

Data from the American Meat Institute (AMI) puts the final demand uses of processed cattle products as an estimated 2.52 billion pounds going into foreign markets and 24.25 billion pounds into domestic markets in 2002 (Otto and Lawrence 2001). These estimates for the various dimensions of the US beef industry at the producer and processor level represent the direct component of the industry with production inputs purchased by these sectors representing the indirect effects. In addition to these obvious producer and input supplying impacts, income earned in these agriculturally-related components of the beef industry is spent in the rest of the economy stimulating a wide range of sectors, including consumer-related businesses in urban areas. This paper used Input-Output (I-O) analysis to show the economic consequences of BSE outbreak in the U.S.

The input-output method is based on the interrelationship between sectors in the economy and how each is affected by a change in the final demand for a sector’s output. The model can be expressed in the following equation:

(1)

where X is sector output, A is intermediate input for sector X usually referred to as the technical coefficient, Y is final demand for sector X, and (I - A)-1 is the Leontief inverse or the multiplier matrix. The multiplier matrix shows the effect of a dollar change in final demand on the sector’s output, a measure of the impact on the economy. Three frequently used types of multipliers are outputs of the sectors of the economy, income earned by household, and employment that is expected to be generated because of the new output. Multipliers can be type I, direct and indirect effects; or type II, direct, indirect and induced effects. To identify andestimate these multiplier effects, an Input-Output (I-O) model is developed for the U.S using IMPLAN 2002 U.S. economic data. The industries were aggregated into 14 major sectors and the output, income and employment multipliers were developed.

Output multiplier for sector j is defined as the total value of production in all sectors of the economy that is necessary in order to satisfy a dollar’s worth of final demand for sector j’s output. The output multiplier is the ratio of the direct and the indirect effect to the initial effect expressed by the following equation:

(2)

where Oj is output multiplier and ij is the Leontief inverse matrix, (I-A)-1 .

The total output is the direct and indirect output effects without including the household. Initial output effect on the economy is simply the initial dollar’s worth of sector j’s output needed to satisfy the additional final demand. Output multiplier is the sum of the column of the Leontief inverse and would show where this spending would have the greatest impact in terms of total dollar value of output generated in the economy.

Income multiplier measures the impact of final demand into change in income received by households. Income multiplier shows the direct and indirect effect of a dollar worth of output in terms of dollar’s worth of new household income. It is expressed by the following equation:

(3)

where, Ij is income multiplier of sector j, an+1 is the income coefficient for each industry (row matrix) and ij is the Leontief inverse matrix.

Employment multiplier measures the relationship between the value of the output of a sector and employment in that sector. The job created per dollar of new final demand for the sector expressed by the following equation:

(4)

where, Ej is employment multiplier, wn+1 is the labor input coefficient for each industry (row matrix) and ij is the Leontief inverse matrix.

Table 1 provides the Type I output multiplier for cattle farming in U.S. Output multiplier indicates the additional output of each sector required for a dollar of new final demand for output in cattle farming. The table presents only the major industries supplying intermediate goods and services. These industries accounted for 83% of any change, an increase or a decrease in final demand for cattle ranching industry. The most affected would be the cattle production and decline in output by a dollar would reduce the industries output by $1.2083, about 54% of the total change. The next industries to be impacted were farming, real estate, animal feed producing industries, and financial services for about 15, 8, 6, and 4% of the total change, respectively. Theindustries which would be affected in terms of their importance to the cattle industry are:financial agencies, power, agricultural and forest support, petroleum, veterinary services, transportation, and wholesale trade. A decline in the demand for cattle products wouldaffect these industries and the economy in general.

*** Insert Table 1***.

BEEF DEMAND EFFECTS

Final demand which includes household, government, and export of beef products in 2002 at 2002 prices was $663.93 million (IMPLAN U.S. Economic data 2002). The import sector was not included in the analysis. To accommodate all the possible scenarios based on the literature, the analysis used 20%, 30%, and 50% BSE-induced reduction in the final demand for the UScattle ranching industry. Under these scenarios it was assumed that no support mechanism (including intervention) was paid to farmers as a compensation for the fall in demand.

The results of the I-O analysis showing the estimates of total output, household income, and employmentfor the economyare presented in Tables 2 through 4. These tables of baseline scenarios for the nation’s cattle industry includes related economic activityofinputsuppliers to the through processing level.

Total industry output measures total dollars of goods and services produced by an industry, including government and non-government activity. Table 2 provides the resultsof thedirect and indirect impact of a decline in final demand for cattle industry on the industry’s as well as output of the rest of the economy. The total value of output generated by thebeef industry and the associated intermediate industries in the U.S. economy would decline with an increase in the reduction of the final demand for cattle industry. The total value of output generated by the cattle industry in the U.S. economy would be $1,192.4, $834.7, and $417.4 million for an increase in the reduction in final demand of 20%, 30%, and 50%, respectively. Gross output declines by 65% for reduction in final demand from 20% to 50%. The major reduction would take place in the cattle industry where the total output would decrease by 54% and farming would be the next highly affected industry, 15%, while real estate and processed animal feed declined by 8% and 6%.

*** Insert Table 2 ***

Table 3 provides the reduction in total household income due to 20%, 30%, and 50% reduction in the final demand for cattle and beef products. The direct and indirect effect of the decline in final demand from 20% to 50% will result in a 65% reduction in total household income. The effect on household income is a little different from the effect on gross output. Even though cattle industry is affected directly by the reduction in final demand,the farming sector providing the feed grains would experience the highest income reduction. The farming industry would have the highest income decline, 26%, followed by the cattle industry, 19%, and the real estate industry, 17%.The income decline in the farming industry was projected to be $97.0, $67.89, and $33.94 million compared to the cattle industry; which would be $69.5, $48.65, and $24.33 million, respectively for 20%, 30%, and 50% reduction in final demand. Other industries to be affected would be energy providers and financial agencies giving loan and other financial services.

***Insert Table 3***

Employment is the other macroeconomic variable that is affected by the change in the final demand. Employment is based on a per unit job consistent with the definitions used by the U.S. Department of Commerce. Table 4 shows the employment impact of a 20%, 30%, and 50% reduction in the final demand for cattleproducts. Employment generated by the cattle industry will decline from about 13.4 million to 4.7 million for a reduction in final demand from 20% to 50%. The distribution of impacts is similar to the pattern for the output indicator as it affects cattle ranching farming most. Cattle production and farming are the two industries that would account for 79% of the reduction in employment; cattle 59% and faming 20%. Ag/forestry support industries and real estate, 9% and 4%, respectively would be the next industries to be affected.

***Insert Table 4 ***

All the macroeconomic variables, output, income, and employment are indicating that the rural economies mainly based on farming and ranching would be affected by any reduction in the demand for cattle related products. The news about BSE has potential to cause concern among the consumers and the cattle industry would be affected via the domestic and export demand. The beef industry is primarily grain-fed beef, and is a major user of feed grains; and factors that affect beef production and price also affects the production and price of feed grain, the grain producers.

CONCLUSIONS

An outbreak of BSE would hurt the US beef industry, other agriculturally-related industry, and the rest of the economy as a whole. The worse effects occur in the beefcattle and farming industries. The present model provides perspective on the potential of BSE to affect the economy. Since the cattle industry is a good source of income for real estate agencies the reduction in business by the industry would have impact on land and other property distribution and income. Generally, the economyof every county would be hurtgiven the fact that cattle are produced in all the 50 states. But it is apparent that the damage would be substantial in those regions and households which already suffer the severest economic damage. These would have serious policy implications for rural economies.