# Factors influencing livestock export in Somaliland’s terminal markets – Pastoralism

### Description of the study area

Somaliland is located in a very arid area with irregular and unevenly distributed rainfalls, both spatially and temporarily, ranging from 100 to 450 mm per annum. There are two wet seasons and two dry seasons. The two wet seasons are Gu (spring) from April to June and Deyr (autumn) from October to December, and the two dry seasons are Jiilaal (winter) from January to March and Xagaa (summer) from July to September.

Historically, extensive livestock production and trade has been an important economic activity in Somaliland where pastoralism and agropastoralism are the main livelihood activities. Livestock trade, especially the export, is one of the main drivers of the country’s economy. There are three lucrative and high-value terminal markets in Somaliland, namely Togwajale, Hargeisa and Burao. These markets are located in the major cities and the capital and close to transport hubs where final buyers transport animals to overseas markets (Umar and Baulch 2007) or slaughter in the major local cities. Togwajale market, which borders Ethiopia, specialises in cattle trade. It is estimated that a large number of the cattle traded in this market originate from the Oromia region of Ethiopia. Hargeisa and Burao markets specialise in small ruminants with most of the animals traded originating from the Somali region of Ethiopia and south-central Somalia. Figure 3 shows the location of the study sites (Hargeisa, Burao and Togwajale markets, and the port of Berbera).

Fig. 3

Map showing study markets and feeding corridors

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### Data sources and analysis

A dataset generated by the Somaliland Chamber of Commerce, Industry and Agriculture (SLCCIA) as part of the Livestock Marketing Information System (LMIS) was used to analyse the factors that influence the monthly number of livestock transacted for export in the study markets. SLCCIA has been systematically capturing the number of animals traded for export (‘export quality’), animal prices and number of exporters active in Hargeisa and Burao markets for small ruminants and Togwajale market for cattle since mid-2007.

Using STATA 13 computer package, a multiple regression analysis was performed to determine the factors that influence the monthly number of livestock traded for export using time series secondary data of the monthly number of livestock traded for export in the three study markets for the period from 2008 to 2017. In addition, normality, autocorrelation, heteroskedasticity and non-stationarity tests were conducted prior to regression analysis. We tested the non-stationarity of the time series data using the Phillips-Perron test (Phillips and Perron 1988). The Phillips-Perron test is preferred for non-stationarity test because it produces consistent estimators of the variance (Rapsomanikis et al. 2003).

### Determination of factors that influence the monthly volume of livestock transacted for export in the terminal markets

A generalised linear model was used to estimate Eqs. (1.1) and (1.2), this is because of the heteroskedasticity problem. We estimated one model for small ruminants and one for cattle because some explanatory variables that affect small ruminants do not affect cattle due to the difference in their value chains and import markets while there is also a significant difference in price and volumes of the two species. Variables and their descriptive statistics are presented in Tables 1 and 2.

Table 1 Descriptive statistics of variables used in the model for small ruminants

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Table 2 Descriptive statistics of variables used in the model for cattle

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#### Model specification for small ruminants transacted for export in Hargeisa and Burao market

The regression model for small ruminants was specified as below:

$$Y={\beta}_0+{\beta}_1{X}_{1t}+{\beta}_2{X}_{2t}+{\beta}_3{X}_{3t}+{\beta}_4{X}_{4t}+{\beta}_5{X}_{5t}+{\beta}_6{X}_{6t}+{\beta}_7{X}_{7t}+{\beta}_8{X}_{8t}+{\beta}_9{X}_{9t}+\upvarepsilon$$

(1.1)

where

Y = monthly volume of small ruminants transacted for export in Hargeisa and Burao markets

β0 − β9 = the estimated coefficients for Xit

X1it = number of active exporters in the markets, X2it = occurrence of Hajj season, X3it = existence of livestock ban, X4it = existence of drought, X5it = access to a quarantine station, X6it = location of the market,X7it = average monthly price, X8t = existence of Australia suspension of small ruminant export to Saudi Arabia and β9X9t = existence of Ethiopia border restrictions

#### Model specification for the cattle transacted for export in Togwajale market

The regression model for cattle was specified as below:

$$Y={\beta}_0+{\beta}_1{X}_{1t}+{\beta}_2{X}_{2t}+{\beta}_3{X}_{3t}+{\beta}_4{X}_{4t}+{\beta}_5{X}_{5t}+{\beta}_6{X}_{6t}+{\beta}_7{X}_{7t}+\upvarepsilon$$

(1.2)

where

Y = monthly volume of cattle transacted for export in Togwajale market

β0 − β7= estimated coefficients for Xt

X1t = number of active cattle exporters in market, X2t = occurrence of Hajj season, X3t = experience of livestock ban, X4t = existence of drought, X5t = access to livestock quarantine stations, X6t = average monthly price and X7t = existence of border restrictions

### Variables and their hypothesised influence on the dependent variable

#### Number of livestock transacted for export in the markets

The monthly volume of livestock traded for export in the study markets was selected as the dependent variable and was estimated as the actual number of heads of cattle and small ruminants transacted in the study markets for the purpose of export to overseas markets during the period under study. SLCCIA collected the monthly volume of livestock transacted for export in the study markets from 2008 to 2017. The volume of livestock marketed was used as an indicator of market performance that is expected to be determined by multiple factors such as the number of livestock exporters active in the markets, occurrence of Hajj season, ban on livestock export, existence of quarantine stations, occurrence of drought, suspension of live animal export to Saudi Arabia by Australia and existence of border restrictions by Ethiopia.

For the independent variables and from the expectations about its positive or negative effects on livestock trade, we have grouped these variables into two groups: variables with expected positive effect and variables with expected negative effect.

#### Number of active livestock exporters

The number of active livestock exporters (ganasade/shirkad in Somali) in the study markets, sometimes represented by their agents (wakiil), was estimated as the number of livestock traders who had purchased animals for the purpose of exporting to overseas markets during the period under study. It was hypothesised that increase in the number of exporters in the markets will positively influence the number of livestock transacted as a higher number of exporters can be an indicator of market competition, more buyers, higher demand, higher price and therefore increase in the number of livestock traded for export in the markets.

#### Occurrence of the Hajj season

This variable was defined as a 60-day period between Eid al-Fitr (also known as Ramadan when Muslims celebrate for the end of their fasting season) and Eid al-Hajj (also known as Eid al-Adha when Muslims celebrate on the 10th day of Hajj). Adha is the practice of slaughtering/scarifying animals in commemoration of prophet Abraham (Umar and Baulch 2007). This study used this variable as a dummy having two categories represented by 0 (normal time of the year) and 1 (the period between Eid al-Fitr and Eid al-Adha). It was hypothesised that the number of livestock transacted for export in the study markets would increase during the Hajj season.

#### Existence of a quarantine station

This variable was defined as the period when official quarantine stations that inspect and certify livestock for export from Somaliland’s port of Berbera were established. This variable is incorporated in the model as a dummy variable having two values: the period before September 2009 was assigned a value of 0 (no official quarantine stations were present to access) and 1 for the period starting from October 2009 when quarantine stations were established in Berbera port. Previous studies reported an increase in livestock export after the establishment of quarantine stations (Khadijah and Kabue 2012; Eid 2014). It was hypothesised that the number of livestock transacted for export increased after the establishment of quarantine stations.

#### Suspension of live animal export to Saudi Arabia by Australia

This variable was defined as the period when Australia, a key small ruminant producer/exporter, suspended its live animal export to Saudi Arabia, the main destination of Somaliland’s small ruminant export. This variable was fitted into the model as a dummy having two values: 0 for the period before the Australia live animal export suspension and 1 for the period starting from 2012 when Australia suspended live animal export to Saudi Arabia. This study hypothesised that Australia’s live animal suspension to Saudi Arabia will have a positive influence on the volume of small ruminants transacted for export in Somaliland since Australia is believed to be a major competitor of Somaliland livestock exports.

#### Average monthly price of livestock

This variable was estimated as the average monthly price of livestock transacted for export in the study markets. Price increase may have both a positive and negative influence on the volume of livestock traded. First, the increase in price may reduce demand in the end markets, and as a result, exporters may buy less livestock. Second, based on the assumption of increased demand in the end markets, traders and producers will market more livestock when the price is higher. In this study, it was hypothesised that the increase in price will lead to the increase in the volume of livestock transacted for export.

#### Ban on livestock export

Experience of export livestock ban was defined as the period when there was an official prohibition of livestock exports from Somaliland’s Berbera port by the import countries. The value assigned to this dummy variable is 1 when livestock export ban was experienced and 0 otherwise. Previous studies reported a significant reduction in the volume of livestock export due to the ban (Umar and Baulch 2007; Eid 2014). It was hypothesised that the number of livestock transacted for export reduced during the period when there was a ban imposed by the import countries, particularly Saudi Arabia which is the main destination for Somaliland livestock export.

#### Occurrence of drought

This variable was defined as failure of expected rain in Somalia (all Somali regions) during the two wet seasons Gu from April to June and Deyr from October to December. The variable was incorporated into the model as a dummy variable having two categories: 0 when there was a no drought (expected rain was received) and 1 otherwise. Previous studies elsewhere in the region showed that drought had a negative effect on volumes of livestock trade due to the increased rate of animal mortality and producers’ effort to recover the herd they lost during drought (Ayele et al. 2006). In this study, it was hypothesised that drought will have a negative influence on the monthly number of livestock transacted for export in the study markets.

#### Existence of cross-border restrictions by Ethiopia

Since 2010, Ethiopia has increased cross-border restrictions of livestock moving towards Somaliland for trade in an attempt to formalise cross-border livestock trade (Eid 2014). This variable was incorporated into the model as a dummy with two values: 0 for period before 2010 when there were limited border restrictions and 1 for the period from 2010 when Ethiopia increased cross-border livestock trade restrictions. This study hypothesised that increased border restrictions will reduce the monthly volume of livestock transacted in the study markets owing to the fact that 50% of small ruminants and over 80% of cattle transacted in study markets originate from eastern Ethiopia.