Lead-Lag Relationships Among Potato Prices at Retail, Wholesale and Farm-gate Markets in West Jav

8/14/2019 Lead-Lag Relationships Among Potato Prices at Retail, Wholesale and Farm-gate Markets in West Jav

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Buletin Penelitian Hortikultura, Tahun 1994, Volume XXVI, Nomor (4)

LEAD-LAG RELATIONSHIPS AMONG POTATO PRICES AT RETAIL,

WHOLESALE, AND FARM-GATE MARKETS IN WEST JAVA

Witono Adiyoga

ABSTRACT

Adiyoga, W., 1994. Hubungan "Lead-Lag" Harga Kentang di Tingkat Pasar Eceran, Grosir danProdusen di Jawa Barat. Analisis harga komoditi kentang berdasarkan data harga bulanan (1980-1986)di ketiga tingkat pasar dilaksanakan dengan menggunakan uji "Granger Causality". Hasil uji

mengindikasikan bahwa pasar di tingkat produsen merupakan sumber informasi harga yang lebihpenting dibandingkan dengan pasar grosir maupun pasar eceran. Kedua pasar yang disebutkan terakhir,kurang efisien dalam mencerminkan informasi baru. Sementara itu, pasar di tingkat eceran ternyata lebihcepat dalam melakukan penyesuaian terhadap informasi harga yang baru dibandingkan dengan pasar ditingkat grosir. Hal ini menunjukkan berkurangnya peranan pasar di tingkat grosir dalam prosespenentuan harga. Variasi kesalahan dalam peramalan harga kentang yang sebagian besar diterangkanoleh inovasi harga di tingkat pasar eceran, menunjukkan bahwa pasar ini bersifat "exogenous". Lebihlanjut juga terungkap bahwa setiap perubahan pada sistem yang terjadi baik dari sisi penawaran maupunpermintaan, akan terasa pengaruhnya setelah tenggang waktu satu bulan. Pengkajian lanjut mengenaiperanan serta efektivitas pasar grosir dalam proses penentuan harga disarankan untuk dapatdilaksanakan pada kesempatan mendatang.

Economic growth in the rural sector has led to an increasing commercialization of agriculturalsector in both factor and product markets and has increased the reliance of the farm community to themarket for resource allocation signals. Marketing research in Indonesia, especially in horticulturalsub-sector, is still considered as one area of research that is not well-developed yet. Previous studies onvegetables marketing were mostly descriptive. They were primarily dealing with the descriptions ofmarketing cost, margin, and channels. Since these studies mostly used cross-section data and assumedstatic nature, they could not provide the basis for implying time-related implications of market behavior.

Consequently, they provided limited information to support the efforts of placing more latitude for pricingpolicy and to take advantage of the use of market signals in driving the growth of this sub-sector.Knowledge of lead-lag relationships among retail, wholesale, and farm-gate prices of a particular

commodity is important in evaluating the margin of packers and retailers. Furthermore, the knowledge oflead-lag structure in various markets could be used to assess pricing efficiency (Adamowicz, Baah &Hawkins, 1984). Evidence of consistent lead-lag relationships could suggest that the leading marketeither has access to more superior information or uses available information more accurately. Thisimplies that the leading market is a more reliable source of market information (Garbade and Silber,1979). Identifying this source of information would be very helpful in providing signals for all agentsinvolve in marketing process, especially for allocating their resources.

The purpose of this study was to assess and interpret the lead-lag relationships among potato prices

at retail, wholesale, and farm-gate level in West Java.


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DATA AND METHOD

The data used in this study were monthly data covering the period of January 1980 to December1986. The three series of prices data represented the monthly average price of potatoes at the retail,

wholesale, and farm-gate level.A vector autoregressive (VAR) process of order p for a system of M variables can be defined as

yt = v + 1 yt-1 +.............+ p yt-p + vt

In this system of M equations,

v = (v1,..............,vM)' is an M-dimensional vector

11,i.............. 1M,iI = .. are M x M coefficient matrices

M1,i.............. MM,i

vt = (vit,............,vMt)' is vector white noise

In deriving the asymptotic properties of parameter estimators, the stationarity of VAR processesmust be considered. According to Judge, Hill, Griffiths, Lutkepohl & Lee (1988), a VAR(p) process isstationary if the time series do not have trends, fixed seasonal patterns, or time-varying variances.

The lag length for the VAR process was determined by using the generalization of the Akaike'sAIC and Schwarz's SC criteria.

2 M2 nAIC (n) = ln det (n) +

T

M2 n ln TSC (n) = ln det (n) +

T

where M is the number of variables in the system, T is the sample size, and n is an estimate of theresidual covariance matrix v obtained by a VAR(n) model.

Causal flows across the markets were tested using the standard Granger F-test:

y2 does not Granger-cause y1, if and only if 12,1 = 12,2 = ..............= 12,p = 0

y1 does not Granger-cause y2, if and only if 21,1 = 21,2 = ..............= 21,p = 0

Those equations are equivalent to the null hypothesis of no Granger causality from y2 to y1 and from y1 toy2, which can be tested by F-test:


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SSEr- SSEu =

p11

where SSErand SSEu are the sums of squared error obtained by estimating the VAR(p) process with andwithout imposing the restrictions, respectively. The null hypothesis of no causal relationship is rejected if > F(p,T-2p-1). Note that for the VAR(1), the F-test is equivalent to t-test for the significance of 12,1.

Meanwhile, to determine which of or to what extent the markets are exogenous or endogenousrelative to each other in the short run, the forecast error decomposition was also examined.

RESULTS AND DISCUSSION

The VAR process is stationary if the roots of polynomial equations are outside the unit circle,implying that there are no fundamental changes in the structure of the process that may render furtheranalysis difficult or impossible. The computation indicated that the roots (root 1 = -1.174 and root 2 =

-2.739) were greater than one in absolute value. Thus, the VAR(1) process is stationary.Up to (p = 4) lag values were examined for the three-equation system considering the time

needed in cultivating potatoes (3 - 4 months). The order of p was chosen so that the AIC or SC criterionwas minimized. It was found that both AIC (= 7.273) and SC (= 7.707) were minimized by VAR(1)process.

The VAR system was estimated by using OLS (Ordinary Least Square). The R2's for thefarm-gate, wholesale, and retail equation were 0.90, 0.87, and 0.93, respectively. The Ljung-BoxQ-statistics indicated that no significant residual auto-correlation was reflected in price adjustmentsbetween markets within the month. The cross-correlations were rPF,PW = 0.89, rPF,PR = 0.79, and rPW,PR =0.82. These implied that the farther was the distance from the production area (farm-gate market), thesmaller was the correlation.

Since the order of the VAR process had been known as VAR(1), the F-test of the causality wasequivalent to the t-test for the significance of 's. The results are presented in the following table:

Table 1 Results of Causality Test Based on the VAR(1) Process

H0 : ij,p = 0 ij,p and SE t-ratio

PW PF 0.18092 (0.21360) 0.84700 Accept H0

PR PF -0.13756 (0.15459) -0.88985 Accept H0

PF PW 1.02830 (0.29248) 3.51570 Reject H0

PR PW -0.41216 (0.18097) -2.27750 Reject H0

PF PR 1.16060 (0.26014) 4.46150 Reject H0

PW PR 0.25833 (0.22240) 1.16150 Accept H0

Note: PF = farm-gate price; PW = wholesale price; PR = retail price

Table 1 shows that there were some causality relationships between the price at the farm-gatelevel and prices at both wholesale and retail level. These indicated that changes in the farm-gate level ledchanges in the wholesale level and changes in the retail level. Meanwhile, feedbacks from eitherwholesale or retail level were apparently absent. These implied that the farm-gate level appeared to bethe source of significant market information, whereas wholesale and retail level might have insufficient

activity to generate much new information. Referring to Garbade and Silber (1979), market at thefarm-gate level was considered as the dominant market.


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Another causality relation was indicated from the price at the retail market to the price at thewholesale market. This indicated that the retail market led the wholesale market in price adjustment tonew information.

The results also indicated that the wholesale market seemed to lose its importance in the pricing

process. It was noted that the causality did not exist from the wholesale market to both farm-gate andretail markets. This might be explained by the amount of potatoes inflow from the production areas to themain consumption area (Jakarta) that was not delivered through the wholesale market (Pasar IndukKramatjati) before it was distributed to the retail markets.

Based on the results above, the three price series were also examined by using the forecast errorvariance decomposition. The forecast error variance of a two-step forecast for the farm-gate price was51.12 (8.86 was the contribution of innovations in farm-gate price, 11.39 was the contribution ofinnovations in wholesale price, and 30.87 was the contribution of innovations in retail price). In otherwords, 18% of the forecast error variance of farm-gate price was accounted for by own innovations, 22%was accounted for by wholesale price innovations, and 60% was accounted for by retail price innovations.Referring to Bessler (1984), the retail market was considered to be exogenous, since the major portion of

forecast error variance was explained by the retail price innovations. However, this information should beused cautiously because the correct interpretation of such decomposition was usually difficult to obtainsince the decomposition itself was not unique (Judge et al., 1988).

CONCLUSIONS

From the Granger causality tests, the results suggested that the farm-gate market led the wholesaleand retail markets in price adjustment to new information. This implied that the farm-gate market was thesource of significant market information, whereas wholesale and retail markets were less efficient inreflecting market information. Unidirectional causality from the retail market to the wholesale market wasalso suggested from the test results. Meanwhile, no causality was indicated from the wholesale market toboth farm-gate and retail markets. These implied that the wholesale market seemed to lose itsimportance in the pricing process. Therefore, the evaluation of the role and effectiveness of the wholesalemarket (Pasar Induk Kramat Jati) was recommended for further study.

The findings also indicated that any changes occurred in the system, either on the supply side oron the demand side would be felt throughout the system within one month. Furthermore, the retail marketwas considered to be exogenous, since the forecast error variance was mostly explained by its priceinnovations.

REFERENCES

Adamowicz, W. L., S. O. Baah & M. H. Hawkins. 1984. Pricing efficiency in hog market. Canadian Journalof Agricultural Economics, 32: 462-477.

Bessler, D. A. 1984. Relative prices and money: A vector autoregression on Brazilian data. AmericanJournal of Agricultural Economics, 66(1): 25-30.

Garbade, K. D. and W. L. Silber. 1979. Dominant and satellite markets: A study of dually traded securities.The Review of Economics and Statistics, 61: 455-461.

Judge, G. G., R. Hill, W. Griffith, H. Lutkepohl & T. Lee. 1988. Introduction to the theory and practice ofeconometrics. Second Edition. John Wiley & Sons, New York.

Documents

Lead-Lag Relationships Among Potato Prices at Retail, Wholesale and Farm-gate Markets in West Jav