Intervention Models Applied to Evaluate Impacts of ...

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Intervention Models Applied to Evaluate Impacts of Sanitary and Technical Barriers to Trade Sílvia H. G. de Miranda Geraldo S.A. de C. Barros ESALQ – University of Sao Paulo 2- 5 th December 2006 Winter Meeting - IATRC

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Intervention Models Applied to Evaluate Impacts of Sanitary and

Technical Barriers to Trade

Sílvia H. G. de MirandaGeraldo S.A. de C. Barros

ESALQ – University of Sao Paulo

2- 5th December 2006Winter Meeting - IATRC

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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

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IntroductionChallenge: 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 frequencyindexes; CGE models, tariff equivalents, gravity models etcOnly a few studies in developing countries

Beef sector: one of the most affected

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International beef market

Brazil - Since 2004: the major exporter2005: US$ 3.1 billion of exports

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

Competition and the Pacific Rim market: quality requirements

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Brazilian beef exports, by type (1000 thousandtons 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

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Beef market requirements consiston barriers to trade?

Brazilian studies:Procópio Filho (1994): sanitary and environmental issues are used todecrease 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

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Relevance HypothesisSanitary and technical events affect Brazilian beef exports, on quantity or prices, or even both

ObjectiveThis study proposes a (econometric + intervention) methodology to measure the impacts of sanitary or technical events on the Brazilian beef exports.

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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 substitutesthere is no perfect substitution in the beef international market

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Structural model for Brazilian exports

SI = f (PI, PB, WI) domestic beef suplyDI = 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 marketYI = shifts of domestic demand;

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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

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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)

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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

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Transfer Function and Intervention Variable

Transfer function Intervention Variable

ω(B) = moving average operator with l termsδ(B) = an auto-regressive operator with m termsZt a stochastic processXt = the explanatory variable responsible for part of the changes occurred in ZtNt is the error term (residue), represented by the second term in the right sidelag b = the moment the explanatory variable starts to influence Utintervention variabel εt

tbtt aBBX

BBwcZ

)()(

)()(

φθ

δ++= − btB

B−ε

δω

)()(

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Representation of intervention variables

A special case of Transfer function

Pulse or step

Vandaele (1983): dynamic effects of intervention variables

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DataFrom 1992 January to 2000 December

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

A Survey: 10 exporting slaughterhouses werevisited:

In 2000, these companies were responsible for 70.1% (value) and 66.5% (volume) of the Brazilianbeef exports (in natura).

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Intervention variables1995 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;

2000May: 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 naturabeef exports because of FMD problems.

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Results

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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

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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

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Intervention ModelJanuary 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.

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Concluding remarks: beef market and intervention analysis

Economic variables were the most significant: expected effects

There is evidence that Brazilian beef exportersface 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 thesignificant residues (outliers)

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Concluding remarks: about modelling

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

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CEPEA – Center for Advanced Studies on Applied Economics

ESALQ- University of São PauloBrazil

Sílvia Miranda: [email protected]

Geraldo Barros: [email protected]