Intervention Models Applied to Evaluate Impacts of Sanitary and

Technical Barriers to Trade

Sílvia H. G. de Miranda

Geraldo S.A. de C. BarrosESALQ – University of Sao Paulo

2- 5th December 2006

Winter Meeting - IATRC

Summary

1. The challenge of measuring non-tariff barriers and the Brazilian beef exports

2. The Econometric model

3. The Intervention Model

4. Results and Concluding Remarks

Introduction Challenge: the measurement of impacts of

sanitary and technical trade barriers

Laird (1996) and Beghin and Bureau (2001): a search of methods Inventory models; coverage and frequency indexes;

CGE models, tariff equivalents, gravity models etc Only a few studies in developing countries

Beef sector: one of the most affected

International beef market

Brazil - Since 2004: the major exporter 2005: US$ 3.1 billion of exports

Other world’s largest exporters: USA, Australia, New Zealand, Argentina and EU a huge protectionism

Competition and the Pacific Rim market: quality requirements

Brazilian beef exports, by type (1000 thousand tons carcass-equivalent). 1990 to 2005

0 200 400 600 800

1000 1200 1400 1600 1800

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Mil toneladas equivalente-carcaça

Processed In natura Total

Source: ABIEC

Beef market requirements consist on barriers to trade?

Brazilian studies: Procópio Filho (1994): sanitary and

environmental issues are used to decrease prices

Ferraz Filho (1997): sanitary rules affect exporting growth rates of companies;

Lima, Miranda & Galli (2005): Brazil is not participating in a beef market amounting to US$ 7.5 billion

Relevance Hypothesis Sanitary and technical events affect

Brazilian beef exports, on quantity or prices, or even both

Objective This study proposes a (econometric +

intervention) methodology to measure the impacts of sanitary or technical events on the Brazilian beef exports.

Econometric Model for External Beef Sales A reduced form model is estimated based

on a structural model;

Assumptions: the imported and domestic goods are not

perfect substitutes there is no perfect substitution in the beef

international market

Structural model for Brazilian exports

SI = f (PI, PB, WI) domestic beef suply

DI = g (PI, YI,) domestic beef demand

SI = volume of beef supplied by domestic market; PI = domestic price for Brazilian beef (in R$); PB = Brazilian beef exporting price (R$); WI = domestic supply shifts; DI = beef volume demanded by domestic market YI = shifts of domestic demand;

XS = SI – DI = h (PI, PB, WI, YI) Xs 0

XD = m (PB/TC, PW, ZD)

XS = volume of Brazilian beef supplied to the international market;

XD = volume of Brazilian beef demanded by the international market;

TC = exchange rate (R$/US$); PW = beef price of competitors in the international market

(US$); and, ZD = shift of the foreign demand of Brazilian beef.

PX = PB/TC => PX = US$ price of the exported Brazilian beef

In a balanced international market, the Brazilian exports follow: X* = XS = XD

X* = equilibrium quantity of Brazilian foreign sales

Reduced Forms:

The equilibrium price for foreign sales X*:

PB = p(PI, WI, YI, TC, PW, ZD)

And the equation for exports volume is a function of:

X* = H (PB, PI, TC,WI, YI, PW, ZD) (1)

Assumption: Perfectly elastic international demand

PX = PB/TC = h(PW, ZD) (2)

a) OLS to estimate the reduced formsb) Residual analysis to identify outliers:

- application of a Box-Jenkins model; - the residues as the dependent variable

Transfer Function and Intervention Variable

Transfer function Intervention Variable

ω(B) = moving average operator with l terms (B) = an auto-regressive operator with m terms Zt a stochastic process Xt = the explanatory variable responsible for part of the changes

occurred in Zt

Nt is the error term (residue), represented by the second term in the right side

lag b = the moment the explanatory variable starts to influence Ut

intervention variabel t

tbtt aB

BX

B

BwcZ

)(

)(

)(

)(

btB

B

)(

)(

Representation of intervention variables A special case of Transfer function

Pulse or step

Vandaele (1983): dynamic effects of intervention variables

Data From 1992 January to 2000 December

In natura exports – to EU* Corned beef – to EU and US

A Survey: 10 exporting slaughterhouses were visited: In 2000, these companies were responsible for

70.1% (value) and 66.5% (volume) of the Brazilian beef exports (in natura).

Intervention variables

1995 March: EU ban temporarily SP and MG beef exports; 1996 March: EU bans imports from UK; 1998:

March: FMD outbreaks in Mato Grosso do Sul State – BR;

May: RS and SC states declared free from FMD with vaccination;

June: partial opening to the UK beef exports to EU; October: FMD outbreak in Naviraí/MS;

2000 May: Argentina, RS and SC were recognized as FMD

free zones without vaccination by the OIE; August: FMD outbreaks in Jóia/RS; September: FTAA lifted bans on Argentinean in natura

beef exports because of FMD problems.

Results

Table 1. Results of Brazilian exports model. Beef special cuts to the European Union (vdtue). 1992 January - 2000 December. Series in level

Model: F(9,97) = 79,05* 2R = 0,88 Dependent variable = LVDTUE

Variable Coefficient Test “t”

Constant 18,04* 4,62

ltxreal t-1 0,72* 2,51

lvdtue t-1 0,44* 6,92

Lrpbrarg -0,10 -0,47

lrbras t-1 -0,90** -2,20

lprdiant t-1 -0,23 -0,99

Lpbreal -1,06* -3,09

lvxarg t-1 -0,46* -3,04

Seasonality 0,23* 4,23

Trend 0,0075* 3,77

Modelo: Q(24,1) = 24,89* 2R = 0,92 Variável dependente =

LVDTUE1

Variável Coeficiente Teste “t”

Constante 25.62* 4.41 AR(1) 0.28** 2.16 N_SAZ{0}2 0.13 1.28 N_SAZ{1} 0.008 0.05 N_SAZ{2} 0.12 0.89 N_SAZ{3} 0.46* 3.15 N_SAZ{4} 0.62* 3.92 N_SAZ{5} 0.60* 3.10 N_SAZ{6} 0.70* 3.57 N_SAZ{7} 0.43* 2.24 N_SAZ{8} 0.19 1.26 N_SAZ{9} 0.15 1.19 N_SAZ{10} 0.08 0.73 N_LTXREAL{1} 0.59 1.27 N_LVXARG{1} -0.48** -2.47 N_LPBREAL{1} -0.80 -1.46 N_LRPBRARG{0} -0.23 -0.77 N_LPRDIANT{1} -0.47 -1.50 N_LRBRAS{1} -1.62** -2.17 N_TREND 0.002 0.12 N_D0195{0} -0.76* -2.90 N_D0195{1} 0.52** 2.13 N_D0396{1} -0.01 -0.06 N_D0396{2} -0.35 -1.27 N_D0396{3} 0.03 0.12 N_D07{0} 0.32*** 1.75 N_D07{1} 1.42* 4.41 N_D07{2} -0.44 -1.39

Table 2. Results of Box-Jenkins model for Brazilian beef exports, special cuts to the EU (vdtue). January 1992 to December 2000

Intervention Model January 1995 statistically significant: shock defined as (m,l,d) = (0,1,0),

where m is the auto-regressive component, l is the moving average component and d is the lag. The result shows an immediate intervention impact, valued in a decrease of

0.76% on vdtue; in t+1 a positive effect on exports, decreasing it in 0.52%

- +1

Jan/95 Fev/95 0 (0,52) - 0.76 - 1

Figure – Sketch on the pattern of the intervention variable (step) effects on Brazilian beef exports to the EU (vdtue ) for January 1995.

Concluding remarks: beef market and intervention analysis

Economic variables were the most significant: expected effects There is evidence that Brazilian beef exporters

face a non perfeclty elastic demand in the EU market: Brazil affects prices

Sanitary events had some significant impacts on quantity and prices of Brazilian beef exports But It was not possible to explain all the significant

residues (outliers)

Concluding remarks: about modelling

The intervention model requires detailed knowledge about the determinants of trade and all the possible relevant events that can affect the sector’s performance

Some additional comments: What is the proper pattern of the intervention function in each

specific case? Regionalized effects? The occurrences coming just after a previous event analyzed

can reduce its original impacts. Update of this study

CEPEA – Center for Advanced Studies on Applied Economics

ESALQ- University of São PauloBrazil

Sílvia Miranda: smiranda@esalq.usp.br

Geraldo Barros: gscbarro@esalq.usp.br