A Macroeconomic Analysis of the Brazilian Coffee Prices

Matheus Vitti de Aguiar

Mirian Rumenos Piedade Bacchi

Abstract: Despite the strong appreciation of the exchange rate, started in 2004, the Brazilian

agribusiness exports maintained a growth trend until 2009. Coffee, despite its relative loss in

Brazilian agribusiness exports, is still an important export product. This paper, based on the

theoretical model of Frankel (1986), Frankel (2006), and its adapted version to the general

Brazilian farm prices by Spolador et al. (2010), aims to analyze and measure the effects of the

Real Interest Rate Difference (Brazil and United States), the real effective exchange rate, and

GDP Brazil on the coffee prices on Brazilian farmers (IPR-Coffee).

Keywords: Macroeconomics, Prices, Commodities, Monetary Policy, Exchange Rate

Policies, Income

1. Introduction

Agribusiness has always been an important sector for Brazilian economic

development, since it contributes to the internal macroeconomic balance (food supply and

price stability), and external (foreign exchange generation).

We can see in Figure 1, that the Brazilian agribusiness had a significant growth in the

period of 1994 to 2008, although in this same period it has been facing adverse

macroeconomic conjunctures, such as overvalued exchange rate and high interest rates.

Figure 1: GDP evolution of Brazilian agribusiness, (R$ billion) from 1994 to 2008.Source: Cepea - ESALQ/USP (www.cepea.esalq.usp.br) and author’s elaboration.

The real Agribusiness’ GDP growth is associated with the development of the

production level, related to gains in productivity of crops and livestock, and to the growth of

foreign markets.

More recently, from 2002/2003, the growth of world economy, and the high levels of

commodity’s international prices, were important factors for the expansion of Brazilian

agribusiness exports, as shown in Figure 2.

Figure 2: Evolution of Brazilian Agribusiness exports, (R$ billion) – from 1996 to 2008.

Source: SECEX/MDIC (www.mdic.gov.br), MAPA (www.agricultura.gov.br) and author’s elaboration.

Brazil, traditionally, has in general always been a relevant exporter of commodities in

general and, particularly, a major coffee exporter. Historically, Brazil has always been, and

remains being, a major producer of coffee, as shown in Figure 3, which presents the Brazilian

and the world coffee production, in tonnes, in the period between the years 1852 and 1991.

Figure 3: Brazilian and world coffee production, in tonnes

Source: IPEA (www.ipeadata.gov.br) and author’s elaboration.

According to Bacha (1992), the portion referring to Brazilian production in the world

total is declining not only because Brazil is no longer in its prime productive – although its

production is still significant, but also due to the large number of competitors who are

currently on the international market, many of them following the standards of quality

internationally determined more rigorously than Brazil, causing a loss of competitiveness in

the world market.

Aiming to analyze the relationship between agricultural commodities and monetary

policies an econometric model based on Frankel (1986) and Frankel (2006) was elaborated,

which will be developed in subsequent chapters.

2. The effect of macroeconomic variables on agricultural prices

The influence of Exchange rate on agricultural prices is noted by Orden e Cheng

(2005), who also highlights the consequent influence on agricultural policies. According to

the results, the indirect effect of the overvaluation of the exchange rate has potentially taxed

the agricultural sector. However, the magnitude of the effects tends to be lower when the real

exchange rate moves closer to its equilibrium value. Nevertheless, the impact of the inclusion

of budgetary payment to the agricultural sector in the indirect effects of the exchange rate on

the same sector can be different depending on the direction of misalignment of the exchange

rate: when the exchange rate is overvalued, the agricultural sector faces a situation of less

protection; and when the exchange rate is undervalued, the sector finds itself more protected.

Hughes and Person (1985 apud ARRUDA, 2008) and Rausser et al (1986) have

focused on the reaction of agricultural and non agricultural products and on increases in

money supply, which cause an increase in interest rates to contain possible inflationary

pressures. This increase in interest rates makes the country attractive for foreign investments

due the improvement in the return rate, and this inflow of foreign capital cause the

appreciation of the exchange rate. Once in a scenery of overvalued exchange rate, the

agricultural products prices tend to absorb more the impacts of the aforementioned increase in

money supply than non agricultural products price, i.e. this exchange rate appreciation leads

to an overshooting of agricultural products prices, suggesting a tax on them.

Frankel (1986 apud ARRUDA, 2008) also addressed the existence of an overshooting

caused by macroeconomic variables, such as changes in exchange rate policies or monetary

policies, on the price of agricultural commodities. According to the same author, this effect

occurs to maintain the expected return of storage compatible to the return achieved in the

financial market. For instance, if the interest rates fall as a result of an expansion of money

supply, the nominal prices of commodities would increase more than proportionately in order

to reduce the expectation of excessive increase in long term inflation rate, matching the edge

of the sector to a lower interest rate.

Barros (1989a apud ARRUDA, 2008) adds that this would occur even in a closed

economy, since the unexpected increase in money supply would generate an expectation of

inflation. Due to this expectation, the investors would be induced to trade currencies for

commodities, increasing the demand for products of the agricultural sector, which would lead

to the rise of their price of them. The effects on an open economy would be very similar.

Barros (1989b apud ARRUDA, 2008) elaborated a model based on Sayad (1979),

Modiano (1985) and Barbosa (1987), in order to determine the correlation between some

macroeconomic factors and Brazilian agricultural prices. The model proposed an economy

composed of two sectors, one agricultural and one industrial. In the model, the Brazilian

economy presented with a high degree of indexing.

Yet according to the model of Barros (1989b) the agricultural sector would produce

both tradable goods and non tradable goods. The price of the first would be determined by

international markets (Brazil as price taker) and the price of the last would be determined by

supply and demand. As far as the industrial sector is concerned, it’s considered to be an

oligopoly that makes prices by adding a margin to the unit production cost. It’s also

delineated that the inputs used in the production are imported.

Barros (1989b) showed that an expansionary shock in money supply causes an overall

effect of favoring agricultural prices to the detriment of industrial prices. Already a

derogatory impact on the exchange rate varies according to the proposed scenario of indexing.

In one of them, industrial prices increase more than agricultural prices, perhaps by the fact

that industrial prices have suffered indirectly with the increase in agricultural prices, besides

the increase of cost from the import of inputs. In another scenery of indexing, agricultural

prices should increase more than industrial prices. With a shock that increases the

international prices of commodities, but keeping constant the price level, the overall effect is

the relative increase in the prices of agricultural products. Lastly, a positive shock in the

domestic supply of agricultural products tends to provoke the decrease of the relative prices of

them.

Albert Fishlow and Edmar Bacha approaches the different ways a country of Latin

America uses its abundance in natural resources to develop itself in the article “Recent

Commodity Price Boom and Latin American Growth: More Than New Bottles for and Old

Wine? In it, the authors make a comparison among four Latin American countries: Argentina,

Chile, Venezuela and Brazil, reporting a little of the economic history of each one and

indentifying the relationship between macroeconomic policies, public policies, commodity

prices and their effect on the country’s economy.

Fishlow and Bacha (2010) also emphasize that since the end of XIX century until 1930

the Brazilian economic story was tied to coffee. Since then, the country has successfully

industrialized, having as pillars the internal market in full growing and the diversified export,

so that coffee represents a small fraction of total amount exported by the country. An error,

according to the authors, that Brazil committed was to be late in replacing the strategy

exclusive for the development through the import substitution, but, thanks to reforms targeted

to the internal market, implemented starting from 1990, the country became an active

participant in the global economic scenario, on which its regarded as an agricultural potency,

not only in the coffee segment, but also in the sugar segment, in the orange juice’s, tobacco’s,

soybean’s, corn’s, meat’s, poultry’s, pork’s. Moreover, the country also stands for oil and iron

production, by its two biggest companies, Petrobras in the first case and Vale in the second

one.

Brazil has been one of the main beneficiary by the boom in international prices of

commodities (Figure 4) that occurred in the beginning of the XXI century to the present day.

In this period, Brazil has been benefited not only from the increase of the price of them, but

also from the growth of the flow of world trade (Figure 5). Also in this macroeconomic

scenery, the domestic currency has been appreciated (Figure 6), even while the Central Bank

accumulated record levels of international reserves.

Figure 4: CRB Index (international price of commodities ) - base 2005.

Source: Thomson Reuters / Jefferies (www.jefferies.com) and author’s elaboration

.

Figure 5: Flow of world trade, in billions of U.S. dollars - from 1994 to 2009.

Source: IPEA (www.ipedata.gov.br) and author’s elaboration.

Figure 6: Real effective exchange rate index - base 2005.

Source: IPEA (www.ipedata.gov.br) and author’s elaboration.

The rising of imports and the slow decline in exports of products not related to

commodities contribute to the current deficit on the Brazilian trade balance, which can

become a problem in the future, as their difficulty in financing. The immediate problem faced

by Brazil is in macroeconomic policies, i.e., a system of floating exchange rates in the context

of an open capital account, and internal interest rates kept in higher levels than those of

external ones in order to maintain inflation under control (FISHLOW, BACHA, 2010).

Fishlow and Bacha (2010) also emphasize that academic studies reveal that besides the

Brazilian macroeconomic problem, the low level of Brazilian savings and government’s

persistent budget deficit, considering that with higher savings and lower deficits, interest rates

could be reduced to lower levels without the risk of inflation run out of control, yet allowing a

more competitive exchange rate. Without this austere control, however, the country seems

doomed to a lower economic growth rate than that of other emerging economies, for instance,

China and India. Brazil managed to pass relatively unscathed from the recent crises of 2009

thanks to the expansionary fiscal and monetary policies, but the persistently high interest rate

and the exchange rate volatility are as an obstacle to higher growth.

In the final remarks, the authors return to the title of the article, the export of

commodities has been a subject of continuous attention and concern from before the

contributions of Raul Prebisch and Hans Singer in the postwar period, however the growth of

large consumer of commodities, as China, India and other Asian countries, as well as growing

importance of pricing based on international scenarios are as new “bottles” on stage.

“Fortunately, during the course of the recent commodity boom, the fiscal spending in nations

that are under development and that are dependent on their natural resources has been much

more prudent than that observed in previous booms” (World Bank, p.9, 2009).

While Bacha and Fishlow (2010) address the impacts of high bid of natural resources

on the process of economic growth and diversification of exports, Souza (2009) empirically

tested the existence of Dutch Disease in Brazil. According to a branch of the literature on

international trade, an expressive increase in the prices of natural resources may cause a

strong growth in revenue from the export of such goods, which would lead to appreciation of

real exchange rate and loss of export and production of manufactured goods competitiveness,

which, in extreme cases, would cause a shrinkage of that sector, a phenomenon known as

deindustrialization; to this set of effects is given the name of Dutch Disease, whose name was

made by the magazine The Economist (1977) in view of the Dutch industrial scenario in 70’s,

whose industrial contraction was attributed to the discovery of large natural gas reserves in

the North Sea in the 50’s and 60’s.

According to the results of Souza (2009), in the period from 1999 to 2008, the data

don’t seem to give empirical support to the hypothesis of Dutch Disease. Measures of

innovation accounting (the function of response to the impulse and decomposition of the

variance of forecast errors), obtained from the estimation of VAR models, don’t show a

significant impact of shocks in commodity prices on the effective rate of exchange. This result

is corroborated by the estimation of VECM model including Brazil commodity index, which

showed no statistically coefficient different from zero to this variable by relating it to the

effective rate of exchange, taking into account several other economic variables. As the CRB

index, which was introduced in the model, the coefficient associated with it has been

estimated as positive and statistically significant, indicating, even in a fragile way, inverse

relationship between the variables.

Souza (2009) also presents the results only to the period from 2003 to 2008, being the

starting year that one from which the effective exchange rate showed a trend of continuous

assessment, in this case the estimates showed a relation of negative significance between the

measures of commodity price and the exchange rate for this time interval, indicating that,

even when taking into account other important variables to explain the performance of

exchange rate, commodity prices contribute to the appreciation of the exchange rate.

Although Souza (2009) has obtained divergent results, the author concludes that these

are not conclusive evidence of the occurrence of the Dutch Disease in Brazil and, according

to Buiter and Purvis (1980), Corden and Neary (1982), van Wijnbergen (1984b), Krugman

(1987), Gylfason et al (1999), Torvik (2001) among others, the problem is more due to the

decrease of production in the tradable goods sector and to vis-à-vis exports than to the

exchange rate appreciation. The evidence that commodity prices in Brazil have been linked to

the appreciation of the effective exchange rate provides only a necessary condition, although

not sufficient, for not rejecting the hypothesis of the problem occurring in Brazil.

Since 2001 the international prices of agricultural commodities suffer a process of

inflation. In Brazil, these effects are also being felt, as the international prices of commodities

rise, begin to compensate the exports by the overvalued exchange rate. Summarizing the

results of Arruda (2008), non-expected increases in the interest rate have the potential to

contain rising prices, the fall of prices can reach two or three times percentage increase of the

interest rate after three or four months. The exchange also has a non insignificant role on the

price, non expected increases of 10% in the exchange rate may elevate, after the same period

as observed for the interest rate, in more than 8% the prices.

In the next sections, it’ll be presented a macroeconomic model, based on Frankel

(1986) and (2006) for determining the coffee price, as well as the methodology that’ll be use

for the econometric estimation of the economic model proposed.

3. Methodology

The objective of this research is to identify the effects of macroeconomic variables

such as, for example, the difference between the real interest rate of Brazil and the

international interest rates, the real effective exchange rate, Brazil’s GDP and The GDP of

agribusiness, as well as the variable currency on price index to Brazilian coffee producer,

based on the theoretical model proposed by Frankel (1986) and Frankel (2006).

For this, firstly it was made a data a survey of the world agribusiness imports and

world coffee imports. As prices were nominal and in dollars, it was used the Consumer Price

Index U.S. (CPI-US) in order to deflate the values, thus obtaining the total world imports of

agribusiness and coffee, both in real terms. It was also tabbed a series of real Brazilian GDP,

standardizing it to 2009 prices. In order to measure the influence of the interest rates, it was

used the real annual Selic rate, obtained from the nominal monthly Selic rate, converted to

annual and deflated by the General Price Index . Finally, an annual series of the Average Price

Received by Producer, also deflated by the General Price Index.

For modeling, it was taken as base the economic model proposed by Frankel (1986)

and Frankel (2006), and adapted by Spolador et al. (2010) for the study of Brazilian

commodities, which will be presented in section 3.1. For the definition and treatment of the

econometric model, it was used the unit root test, as exposed in section 3.2.

3.1 The economic model

3.1.1 The commodity market

The Economic agents of the commodity market observe the evolution of the real

commodity price in relation to the long-term equilibrium price, as Frankel (2006), and expect

the price to converge to the long-term equilibrium as the expressions (1) and (2)1:

qqqEpsE (1)

Or,

pEqqsE (2)

Being,

s ≡ commodity spot price;

s ≡ long-term equilibrium price;

p ≡ economy general of price index;

q ≡ s-p, real commodity price;

1 All variables are in logarithmic form

q ≡ real long-term equilibrium price.

Commodities are negotiated in international markets, with prices given in U.S. dollars,

so that a small country is a “price taker” in the market. The opportunity cost of storage defines

an arbitrage condition:

icsE (3)

Where,

i ≡ short term nominal interest rate;

c ≡ benefit cost of maintaining inventory.

Combining (2) and (3):

cpEiqq

1(4)

The expression (4) is the main result of Frankel (1986), for it suggests that the effects

of the real interest rate on the real price of commodities are inversely proportional. For a small

country, which receives the price in dollar, it’s necessary to consider also the exchange rate,

which will be included in the model in section 3.1.4.

3.1.2 The goods market

In Frankel (1986) model, the author admitted that the level of prices of manufactured

goods can be adjusted by the excess of demand, from a traditional Phillips curve:

mm ydp (5)

Being,

mp = logarithmic form of the manufactured goods price;

d = logarithmic form of demand for goods;

my = logarithmic form of potential output;

μ = expectative of currency growth rate.

It’s assumed that in the long term there is no excess of demand, so, Frankel (1986)

defined that the excess of demand is a function of the rising of commodity prices relatively to

manufactured goods prices and interest rate:

ripqyd mm (6)

r is a constant term.

Replacing (6) in (5):

ripqp mm (7)

3.1.3 The money market

Frankel (1986) defined demand for money as:

iypm (8)

m = logarithmic form of the money supply;

p = logarithmic form of the general price level;

y = logarithmic form of the total product;

λ, = are demand elasticities for money related to the product, and the semi demand

elasticity for money related to the interest rate, respectively.

The nominal interest rate in the long-term (i ) converges to r , and the exogenous

factors that determine the relative prices are:

rymppq m , (9)

Based on equations (4) and (9), we can obtain the full expression that represents the

dynamic of commodity prices:

cpEirymq

1(10)

3.1.4 The inclusion of the exchange rate

Based on section 3.1.1, we can conclude that commodity prices are determined in

international markets, and given in dollar. For any other country except United States is,

therefore, necessary to consider the exchange rate.

Frankel (2006) showed that the spot price of a commodity in the currency j is:

cjj sss /$$/ (11)

Where,

$/js = exchange rate (currency j per US$);

cs /$ = spot price of the commodity c in US$.

Based on overshooting model of Dornbusch (1976), Frankel (2006) obtained the

following expression:

$$$$$/$/

1pEpEii

vppppss jjjjjj

(12)

From the expression (11) we obtain:

cccjcjjj ssssss /$/$//$/$/ (13)

Replacing (13) in (12):

$$$$/$/$//

1pEpEii

vppppssss jjjjcccjcj

By definition of section 3.1.1:

cjcj ss // -

jj pp = cjcj qq //

And,

cc ss /$/$ - $$ pp = cc qq /$/$

So:

$$/$/$//

1pEpEii

vqqqq jjcccjcj

(14)

From expression (4):

cpEiqq cc

$$/$/$

1

And, replacing (4) in (14):

11$$$$// cpEipEpEii

vqq jjcjcj

crrrv

qq jcjcj

$$//

11

(15)

The expression (15) is the result of Frankel (2006) with the addition of the exchange

rate overshooting effect on the commodity prices. Combining the expressions (9) and (15),

the relevant expression to the study of the received prices by the Brazilian producers, in this

research, is:

crrrv

rymq jcj

$$/

11

(16)

By the expression (16) we can realize that an increase in the money supply will lead

to an increase in commodity prices. However, if the price of manufactures goods are sticky in

the short term, the real interest rate will tend to be reduced in the long term. Therefore, there’s

an inversely proportional effect between the interest rates and the commodity prices.

In the following section it’s presented the econometric model to estimate the effects of

the relevant variables of the economic model, determined by the expression (16), on the

coffee prices on Brazilian farmers (IRP-coffee), in the period from 1970 to 2007.

3.2 Econometric procedures and model justification

3.2.1 The unit root test

The unit root test, according to the method proposed by Dickey & Fuller (1981), is

enshrined in the economic literature of time series; that’s why it’ll be presented briefly in this

section, which text is all based on Enders (2004). In Dickey-Fuller test we determine the order

(p) of the autoregressive process that generates the series, as the criteria of Akaike (AIC) and

Schwartz (SBC). The number of lags that presents the lowest values for AIC and SC criteria

will represent the most suitable model.

The statistics of the AIC and SBC criteria are represented by the following

expressions:

NAIC

2ln

2

N

NSC

ln2ln

Where 2

is the sum of squared residuals estimated in the autoregressive process of order p,

and N is the number of observations of the sample.

According to Enders (2004), the Dickey-Fuller unit root test is performed in six

steps:

1) We define and estimate an autoregressive model with the lags determined by the Akaike

and Schwarz criteria, as the expression (17):

1p

1ititi1tt xxtx (17);

2) Through statistical, of the table of Dickey & Fuller (1981), we test the hypothesis that =

0. If the null hypothesis is rejected, we use then statistical to test the hypothesis that = 0,

if rejected, leads to test = 0 again, but considering the normal distribution;

3) If the hypothesis that = 0 isn’t rejected, it’s estimated a new model without trend, but

with and intercept, as the expression (18):

1p

1ititi1tt xxx (18);

4) From the expression (2), we test the hypothesis that = 0 based on the statistical. The

non rejection of this hypothesis leads to the test that = 0, considering the statistical being

that, giving the rejection of the hypothesis, we test = 0 with the normal distribution;

5) If the hypothesis that = 0 isn’t rejected, we estimate an autoregressive model without

interception or trend, according to the expression (19):

1p

1ititi1tt xxx (19);

6) After the first five steps, we test the hypothesis that = 0 based on statistical. In case of

accepting this hypothesis, we conclude the generator process of the series in question has a

unit root, and the series will be used in the econometric model in differences.

3.3 Definition of the econometric model

For the definition of the econometric model some data series were tabulated, based on

the theoretical model of Frankel (1986) and Frankel (2006), to come up with an econometric

model that allows analyze the effect of macroeconomic variables on the received price by the

Brazilian coffee producers. The selected variables are in the Table 1.

Table 1 - Consolidation of the variables used, periodicity and source

Variable Periodicity Source

Real average price received by producer (R$/Kg) Annual (1970 to 2007) Ipeadata

Real Interest Rate Difference (BR and USA) - % py Annual (1970 to 2007) Ipeadata

Real value of world coffee import (thousand US$) Annual (1970 to 2007) FAO

Exchange rate (R$/US$) Annual (1970 to 2007) Ipeadata

Agricultural GDP (million R$) Annual (1970 to 2007) Ipeadata

Money supply (M1) (million R$)

Production quantity (index based on year 2007)

Productivity (tones/hec)

Annual (1970 to 2007)

Annual (1970 to 2007)

Annual (1970 to 2007)

Ipeadata

Ipeadata

Ipeadata

Source: author’s elaboration.

Therefore, starting from the selected variables and from the theoretical model of

Frankel (1986) and Frankel (2006), the estimated econometric model is defined as:

tttttt ellymoneyrateexchangeGDPimportrateerestcice sup___intPr

Considering et, the random term with average zero and constant variance.

All variables expressed in monetary units were deflated, in the case of variables

expressed in R$ the used deflator was the IGP-DI (Brazilian General Prices Index).

The interest differential represents the difference between the real interest rate in

Brazil, Selic rate deflated by the IGP-DI, and the interest of U.S. federal founds deflated by

U.S CPI.

In order to calculate the real exchange rate it was taken the nominal exchange rate

(R$/US$) and it was calculated the real exchange rate using the IGP-DI and the U.S. BPI

In the following section it’ll be presented the obtained results according to the

methodology described in section 3.

4. Analysis and discussion of results

The Akaike and Schwarz criteria (AIC-SBC) were performed to define the lags of the

variables in the unit root tests, and the results are shown in the Table 2. The variables, except

for the interest differential, were worked in logarithmic form.

Table 2 – Results of Akaike and Schwarz criteria.

Variables AIC SBC

Coffee price received index 1 1

World Coffee Import 6 1

Interest rate 3 3

Exchange rate 2 1

Agricultural GDP 1 1

Money supply(M1) 5 5

Source: research data.

In Table 3, the results of the unit root tests are presented. At the significance level of

5%, exception made for GDP and world imports of coffee, no other variable showed itself

stationary in level. However, all other variables became stationary in the first difference

being, therefore, integrated of order 1, in other words I (1).

Table 3 – Unit root tests.

VariablesModel 12 Model 23

tt tbt tm tam t t

Coffee price received index -3.384 -2.712 -1.889 1.693 -0.831 -4.599

World Coffee Import -3.809 -3.886 -0.385 0.256 -1.184 -3.375

Interest rate -2.194 1.438 -1.629 0.793 -1.437 -4.821

Exchange rate -2,447 -2,161 -1,338 1,098 -0,978 -2,698

Agricultural GDP -2,275 -0,378 -2,275 2,290 0,101 -4,609

Money supply(M1) -1,459 1,854 -0,808 0,844 0,451 -2,410

Source: research data.

The Dickey-Fuller procedure is more recommended for large samples, and in this

work the availability of annual data is limited to the period from 1970 to 2007, which is just

38 observations. However, as the unit root tests indicated that the GDP series is stationary, it

was used in level, rather than in difference.

Then the results of the linear regression are presented in Table 4. The results suggest

that the theoretical model proposed by Frankel (1986) and Frankel (2006) is appropriated to

evaluate the determination of prices received by coffee producers in Brazil, between 1970 and

2007. It’s important to detach that even working with the variables in difference, except to

GDP, the coefficient of determination (R²) showed itself high (about 82%), which means that

the econometric model was able to capture the influence of the variables on the coffee price.

Moreover, to bypass problems associated with auto-correlation of residues a variable

representing the lag of the dependent was included in the model.

The best econometric fit found is that reported in Table 4. The considered GDP was of

the agriculture, therefore an adaptation of the theoretical model of Frankel (1986 and 2006). A

dummy variable to capture the periods of higher coffee prices was also included; the inclusion

of this variable improved the model results.

2Model 1

1p

1ititi1tt xxtx , in versions with intercept and trend, with

intercept and without trend, and in the absence of both.

3 Model 2 t, set after the tests verify the absence of deterministic terms.

Table 4 – Estimates of the econometric model.

Variable Coefficients T-Test Significance Level

Constant 0,736 1,657 0,109

Trend 0,001 0,426 0,673

Price received by producer {-1} -0,277 -2,963 0,006

World coffee import 1,080 6,641 0,000

Exchange rate {-1} 0,749 2,706 0,011

Real interest rate -0,0003 -0,144 0,886

Brazil real GDP -0,178 -1,866 0,073

Money supply 0,462 3,844 0,000

Dummy variable 0,174 1,558 0,131

R2 81,70%

Source: research data.

The signals of all estimated coefficients are consistent with those expected from the

theoretical model.

The estimated coefficient of the differential in interest rate, albeit with the expected

signal, didn’t present statistically significance. This result is different from the results found

by Frankel (2006) when studying the international commodity market, and also different from

the preliminary results of Spolador et al (2010) for the general index of price by producer

(IPR) in Brazil. However, when doing a graphical analysis, between the price received by

coffee producer and the differential of the real interest rate, there is an inversely proportional

relation between the variables (Figure 7), with a negative correlation of about 33%, although

correlation doesn’t indicate necessarily causality.

The fact of the econometric model doesn’t capture a statistically significant effect of

the differential of interest on the coffee price received may be associated to the chosen interest

rate. It was chosen as a measure of the Brazil’s interest rate the Selic rate, which is the basic

reference rate of Brazilian economy. However, the National Rural Credit System (SNCR) is a

major instrument of agricultural policy in Brazil since the end of 1960’s. In future researches,

it may be necessary to consider the interest rate charged by the credit extended to agriculture.

Another possible interpretation is the fact that coffee is essentially a product of foreign

market, and the fact that Brazil is one of the leading suppliers in the international market, the

prices to producers respond essentially to demand shocks and variables that affect earnings on

exports, as is the case of the exchange rate.

Figure 7: Index of prices received by producer (coffee) and the differential of interest rate (Brazil and United

States) – 1970 to 2007.

Source: IPEA (www.ipeadata.gov.br) and FGV, and author’s elaboration.

It wasn’t observed a contemporaneous effect of exchange rate on the coffee price, but

the result of causality was quite significant with a lag period, as shown in table 7.

Analyzing other coefficients of table 4, it’s identified a direct relation of causality

between world’s coffee imports, the exchange rate and the money supply as far as the coffee

price is concerned. The world import coffee was the variable chosen to represent the world

demand for the product, and estimates suggest that this variable has the effect of greater

magnitude (1.08) on determining the coffee price to Brazilian producer.

The agricultural GDP, as used in the econometric model, captures an effect of

domestic supply on the prices’ behavior and, for this, as anticipated by economic theory,

presented a negative signal. From the magnitude of estimated coefficients of supply variables

(PIB) and demand (world imports), it’s observed that for the case of Brazilian coffee, the

effects of demand are more important than supply shocks.

5. Conclusions

The present work resumed econometric analysis in the behavior of commodity prices,

in the specific case of coffee, in view of some influences of macroeconomic variables, as the

interest rate, world imports of coffee, exchange rate, the agriculture GDP, and the money

supply. The estimated econometric model presented a high explanatory power about the

behavior of prices received by producers of coffee (around 82%).

The reason of this work is on the current macroeconomic situation, in which the

growth of emerging economies increased the demand and, therefore, the international

commodity prices. Domestically, due to the appreciation of the exchange rate, exports of

commodities became essential to avoid an imbalance in external accounts.

The works of Frankel (1986) and Frankel (2006) have provided a theoretical basis for

analyzing the relations between macroeconomic variables and commodity prices. This work is

in addition to analyses of Arruda (2008) and Spolador et al (2010) that seek to evaluate the

impact of macroeconomic variables on the commodities price in Brazil.

Comparing the results found by the estimated model with those found by Frankel

(2006), there are some differences in the effect of the interest rate, which was insignificant in

this one while decisive in that one.

The results of this research are significant as far as the importance of foreign market

and the exchange rate on the determination of price received by coffee producer. The

exchange rate, although didn’t show a contemporary influence, doesn’t contradict the trend of

external determination of prices, once with a lag period the causality showed itself significant.

It was included in the econometric model the agricultural GDP, in order to measure

the effects of supply shocks on the price received. The estimated effects were statistically

significant, although of lesser magnitude compared to demand shocks.

As a suggestion to future researches, it would be interesting to add to the basic

macroeconomic model some sectoral variables such as, for example, granted credit and

productivity, which may increase the accuracy of the econometric model and provide more

information on the determination of prices to producer in the coffee market in Brazil.

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