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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. 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: [email protected]
Geraldo Barros: [email protected]