Analysing Australian exporter performance

This paper presents experimental results of a firm-level analysis of Australian merchandise exporter performance and characteristics, using export declarations and integrated business microdata from the Business Longitudinal Analysis Data Environment (BLADE).

Export declarations are identified by either an Australian Business Number (ABN) or a Customs Client Identifier (CCID). Export declarations with ABNs were linked to the BLADE using the same graph-based method that was employed for the 2019-20 Characteristics of Australian Exporters.¹ This leads to 41,092 linked units in the BLADE, accounting for 99.2% of Australia’s total merchandise export value in 2020.

The study of the linked population (hereafter referred to as the 'population') over the period 2014 to 2020 provides insights into the nature of Australian exporter continuity and resilience during a period of considerable turbulence (challenges associated with trade restrictions, COVID-19, etc.) We found that a relatively large proportion of businesses commenced or ceased exporting annually. In 2020, 11,873 exporters (28.9% of the year-end population) commenced exporting while 29,219 exporters (71.1% of the population) continued exporting from 2019. 13,916 exporters (or 32.3% of the population in 2019) ceased exporting.

17,679 exporters exported every year over the period from 2016 to 2020. These continuous exporters represent 43.0% of the population and 89.2% of the population’s total export value in 2020. The median average annual growth rate of these continuous exporters over 2016 to 2020 was 0.1%, considerably lower than a median average annual growth rate of 5.1% for the same cohort over the period from 2016 to 2019. The difference reflects that an increased number of exporters experienced a decline in their export value in 2020. COVID-19 related restrictions and associated supply constraints could be a contributor to this decline.

Of the continuous exporters, 7,018 exporters or 17.1% of the population were categorised as resilient, their export value in 2020 being equal to, or exceeding, their 4-year average over 2016-2019. They represent 64.8% of the population’s total export value in 2020. Mining exporters account for 1.5% of the resilient population but 70.8% of the resilient population's total export value. Large and medium exporters are more likely to be resilient than small exporters (29.4% and 22.0% of their respective cohorts, compared to 9.5%). Businesses in the older age group (20 years and over) are more likely to be resilient than those in the younger age group (under 20 years). Resilient exporters also had more diversified markets, with 29.9% of the resilient population exporting to more than 5 countries in 2020, compared to just 7.8% of the non-resilient population.

Exports contributed around 22% of Australian GDP in 2020-21.² As international trade is an important contributor to growth in the Australian economy, measuring export performance and gaining insights into factors for export success are of particular importance for government policy makers and researchers.

The ABS’s BLADE microdata contains merchandise monthly trade declarations and firm-level characteristics of Australian businesses.³ For this study, the integrated BLADE data was represented in the form of a knowledge graph, a novel network-like information structure that can efficiently hold the content and associated metadata of massive volumes of heterogeneous multisource data (Clarke and Chien 2015). This Trade Performance Knowledge Graph (TPKG) provides a flexible, semantically enriched view of the underlying BLADE source data, facilitating analysis of firm-level performance and exporter characteristics.⁴

The integrated BLADE microdata was available for the financial years from 2012-13 to 2020-21, with monthly merchandise export declarations from July 2012 to December 2020. Note that certain goods are exempt from requiring export declarations. These include, inter alia: personal effects; consignments of goods that have a value of less than $2,000; Australia Post or diplomatic bags of mail; and military goods that are the property of the Australian Government for use overseas by Australian Defence Forces.⁵

Exporting entities in export declarations fall into two groups. The first group comprises exporters that are identified by an Australian Business Number (ABN). They accounted for 74.2% of total exporters and the overwhelming share (99.2%) of total export value in 2020. The second group comprises exporters that can only be identified by a Customs Client Identifier (CCID). They accounted for 25.8% of total exporters and 0.8% of total export value in 2020. In this study, the linkage of export declarations to the BLADE via ABN was made only for the first group.

The majority of businesses in the BLADE are non-profiled businesses in the ABS Business Register and can be identified by a single ABN. For this type of business, direct one-to-one linkage can be made between an exporting entity in export declarations and a BLADE business unit.

However, there are a relatively small number of businesses with complex structures, which cannot be identified by a single ABN. The ABS profiles this type of business according to its production activity based on the Type of Activity Unit (TAU) concept of the ABS Economic Unit Model.⁶ In this case, an exporting entity in export declarations can be linked to a producing unit identified by TAU.  The linking methodology for this type of businesses is described in Characteristics of Australian Exporters methodology, 2019-20 financial year.

There is a relatively small number of trade declarations where the ABN cannot be linked to the BLADE. As shown in Table 1, such exporters comprise only 0.1% of total exporters or 0.03% total export value.

Due to the lack of an ABN, trade declarations identified by CCIDs cannot be directly linked to a BLADE unit. Therefore, the characteristics of these businesses are unknown.

There has been a steady increase in the use of CCIDs in export declarations during the period from 2013 to 2020. In 2013, CCIDs accounted for 11.4% of the total number of unique identifiers on export declarations. By 2020, this proportion had more than doubled, to 25.8%. While the value share of CCIDs in 2020 remains very low, it is desirable to include CCIDs in the analysis given that they make up over a quarter of the population (Table 1). However, linking of CCIDs to the BLADE is a major challenge, which is beyond the scope of this paper.

There are higher proportions of CCIDs among businesses exporting machinery and transport equipment, classified under Section 7 of the SITC,⁷ and commodities not classified elsewhere in the SITC (40.9% and 39.7% respectively) than the average for all exporters (25.8%).

Because the business characteristics of both CCIDs and those ABNs outside the BLADE are unknown, the rest of this paper considers only the performance and characteristics of the exporter population that we were able to link to BLADE (hereafter referred to as the “linked population”). That is, we have excluded from our analysis all CCIDs and the small number of ABNs that could not be linked to the BLADE. In total, there were 41,092 linked exporters (BLADE units), accounting for 99.2% Australia’s total merchandise export value.⁸

To capture the COVID-19 impacts on exporters in 2020, the study was conducted on a calendar year basis, from 2013 to 2020.⁹

Australian exports are dominated by the mining industry.¹⁰ This is evident in the linked population.¹¹ In 2020, exports by the mining industry accounted for 62.9% of the population’s total export value, compared to 21.2% by the manufacturing industry and 9.3% by the wholesale trade industry. Although mining exports make up almost two-thirds of total merchandise exports, by count mining exporters comprise only a small proportion of the population (1.0%).

Figure 1 shows the year-on-year change (percentage points) in the population’s total export value, by the industry of exporters. As expected, these movements were primarily driven by the mining industry. The decline in 2020 could be explained, in part, by the impacts of COVID-19 related disruptions on international trade and the fall in exports of some commodities to China.

Figure 2 shows that at the aggregate level, the fall in the export value in 2020 was largely driven by a decline in the quantity, rather than price, of exports. Here annual growth in volume was estimated by deflating the total export value by the ABS’s published implicit price deflator (IPD) for total exports.¹²

A relatively large number of businesses commenced exporting or ceased exporting, on the year-on-year basis, over the period from 2014 to 2020. Their proportions relative to the total population are shown in Figure 3. In 2020, 11,873 businesses, or 28.9% of the total population, commenced exporting. 13,916 businesses exported in 2019 but ceased exporting in 2020. These exporters accounted for 32.3% of total exporters in 2019. 29,219 exporters (71.1% of the total population in 2020¹³) continued exporting from 2019.

In interpreting this relatively high churn rate, it is important to consider other factors that could lead to businesses seemingly entering or exiting export markets (entrants and exits). Entrants will include completely new exporters, but may also include, for example: (i) businesses that are re-starting their exports after a hiatus; (ii) businesses that export regularly but less frequently than yearly (e. g. every two or three years); and (iii) a change in ABN to TAU mapping due to a change in the firm’s business structure. Similarly, businesses that have apparently ceased exporting may include businesses that have changed ABNs due to a merger or acquisition, and a change in the firm’s business structure as in (iii).

Figure 3 shows that 2020 was an atypical year: there was both a noticeable increase in the proportion of businesses that ceased exporting and a noticeable decrease in the proportion of exporters that commenced exporting. This latter observation is also apparent in Figure 4.

Nearly three in five (or 62.3%) of those businesses that commenced exporting in 2020 had no previous export history in the past 6 years (from 2014 to 2019). See Figure 5. These businesses were likely to be new exporters. About 14.6% (or 1,731) exported in one year between 2014 and 2018.

By comparison, nearly two in five (or 38.4%) of those businesses that ceased exporting in 2020 had no export history during the past period from 2014 to 2018. See Figure 6. 2019 was the first and only year these businesses had exported since at least 2013. Therefore, they were likely to be opportunistic exporters.

A small proportion of the businesses that commenced or ceased exporting had previously been continuously exporting (Figures 5 and 6). Around 10% (or 1,386) of the exporters that ceased exporting in 2020 had exported continuously every previous year from 2014 to 2019. By contrast, only 3.4% (or 398) of the businesses that commenced exporting in 2020 had continuously exported every year from 2014 to 2018, temporarily ceasing in 2019.

Figures 5 and 6 also show that relatively high proportions of the businesses that commenced or ceased exporting were in the Wholesale and ‘Other’ industry groupings.

We can also classify businesses by the number of prior years over which they have been continuously exporting. As shown in Figure 7, most of the exporters (71.1%) in 2020 had been exporting since at least the previous year (2019). The proportion of continuous exporters relative to the total 2020 population then decreases as one considers longer periods of previous continuous exporting. 33.8% of the 2020 population had exported continuously for at least 6 years. The 2019 population follows a similar distribution.

Continuous exporters are a major driver of sustained growth in Australian merchandise exports. Their performance is thus of particular interest. In this and the following sections, we define “continuous exporters” as those businesses that exported every year over the period 2016 to 2020. There were 17,679 such continuous exporters, representing 43% of the population or 89% of the population’s total 2020 export value.¹⁴

In the literature on export performance, financial (or economic) indicators such as export sales or profits are commonly used for assessing export performance (e.g. Beleska-Spasova 2014). The main rationale for using financial (or economic) indicators is that achieving financial outcomes such as export sales and profit is one of the main goals of an export business. In the following discussion, export value is used as an indicator for export performance.

We analysed exporter performance by comparing the average annual percentage change in their export value over the period 2016 to 2020 versus the period 2016 to 2019. Here average annual percentage change was calculated using the standard compound annual growth rate (CAGR) formula.¹⁵ Differences in the average annual percentage change between these two window periods should reflect average movements from 2019 to 2020. The continuous exporters were also stratified into different exporter cohorts by their characteristics in 2020. The median average annual percentage change was estimated for each cohort and compared across all business cohorts.

In Figure 8 (or Table 2), exporters have been stratified into industry cohorts and then the median average annual percentage change was calculated for each cohort. The table shows that the median average annual change for the entire continuous exporter population over the period from 2016 to 2020 was 0.1%, much lower than 5.1% for that same population over the period from 2016 to 2019. This difference reflects that a large number of exporters experienced a fall in their annual export value from 2019 to 2020, which could be partly due to the impacts of COVID-19 restrictions.

The median average annual growth rate also varies considerably across industries. Exporters from the mining industry generally outperformed the other industries, having the highest median average annual growth rates over each period, 1.5% for 2016-2020 and 11% for 2016-2019 (Table 2).

Exporter performance also varies by exporter size. See Figure 9. The size of an exporting business was defined using the same criteria as the 2019-20 Characteristics of Australian Exporters, based on the number of employees, business annual turnover, and export value.¹⁶ Exporters are classified as ‘large’ if they have:

• 200 or more employees; or
• turnover of $20m or more; or
• exports of $20m or more during the reference period.

Exporters are classified as ‘small’ if:

• their number of employees was fewer than 20 employees or not reported; and
• their turnover was less than $2m or not reported; and
• their export value was less than $2m during the reference period.

All the remaining exporters, that are not defined as large or small, are classified as ‘medium’.

Over the period from 2016 to 2020, large and medium exporters outperformed small exporters. See Table 3.  The median average annual growth rate over that period was 2.4% and 2.0% for large and medium exporters respectively, compared to a fall of 5.0% for small exporters.

Figure 10 (or Table 4) shows that exporters with diversified markets outperformed those that had a single market.¹⁷ Here the number of destination countries was used as an indicator for market diversification. The more destination countries to which a business exports, the more diversified are their export markets. The median average annual change for exporters with a single market was much lower over 2016-2020 than it was over 2016-2019 (-9% versus 0.3%).

Although there are relatively higher proportions of mining exporters in the multiple destination country groups than in the single destination country group, they still represent a small share of the group population. Therefore, mining exporters do not have significant effects on the profiles of median average annual growth rates in Figure 10.

Figure 11 shows the  growth performance of the continuous exporters by main transport mode. A firm may use both sea and air modes. In this case, the main transport mode was identified as the transport mode that accounted for over 50% of a firm’s total export value.¹⁸ 55% of the continuous exporters used sea transport as their main transport mode, compared to 41% of the total population.  Sea transport also accounted for 87% of the export value for the continuous exporters.

As shown in Figure 12, manufacturing exports are dominant by value in goods transported via air (69%) while mining exports are dominant in goods moved via sea (73%).

While both transport modes have similar median average annual growth rates during the period from 2016 to 2019, the median average annual growth rate is negative for the air transport mode when the temporal window is extended to 2020. This indicates that exporters using sea transport performed better than those using air transport in 2020.

To some extent, continuous exporters have already exhibited resilience by continuously exporting through 2020, despite the impact of trade disruptions due to COVID-19-related restrictions and global economic conditions. Among the 17,679 continuous exporters, 7,018 (40%) were identified as ‘resilient’, having a total export value in 2020 equal to or exceeding their average annual export value over the past four years (2016-2019). These resilient exporters accounted for 17.1% of the total exporter population or 64.8% of total export value in 2020.

When exporters are grouped by industry, the proportion of resilient exporters (relative to the industry cohort's total population) varies. Exporters in mining and manufacturing have the highest proportions of resilient exporters (24.1% and 23.2% respectively), as shown in Figure 13. Given that resilient exporters are a subpopulation of the continuous exporters, proportions of continuous exporters (also relative to each cohort's total population) are shown in Figures 13-17 for comparison. As expected, the profile of resilient exporters closely follows that of continuous exporters.

Note that mining exporters represent only a small proportion of the resilient exporters (1.5%) but account for 70.8% of their total export value.

Figure 14 shows proportions of resilient exporters by business size and age. Exporter age is defined as the number of years from when the business was established (not the time from which the business started to export).

In general, large and medium-sized exporters have higher proportions of resilient exporters than small-sized exporters. Proportions of resilient exporters also vary by age groups. Of the medium sized exporters, the proportion of resilient exporters within the age group of 20 years and over is higher than the age group under 20 years (27.2% compared to 21.4%). A similar difference between those two age groups can also be seen for small exporters (15.0% compared to 10.8%).

As shown in Figure 15, exporters with higher export frequency¹⁹ were more likely to be resilient than those with lower export frequency (for example, 44.9% of the exporters with a frequency of 51 or more export declarations in 2020 were resilient, compared to just 2.4% of the exporters with a frequency of fewer than 3 that year).

Figure 16 compares exporters by market diversification. Exporters with 6 or more destination countries were more likely to be resilient than exporters with single destination country: 44.1% of the cohort population versus 6.8%.

With respect to the main transport mode (Figure 17), the profile of the resilient exporters is again similar to that of the continuous exporters. The resilient proportion of the cohort using sea as its main transport mode was higher than that of the cohort using air (19.7% vs 14.4%).

Restricting the scope to the exporter population linked to business characteristics in the BLADE, this study focused on the “continuous exporters” – who are defined as exporters that lodged at least one export declaration in each year from 2016 to 2020 (inclusive). These continuous exporters accounted for the predominant share (89%) of the linked population’s total merchandise export value. Unsurprisingly, they were also the main driver of the year-on-year movements in that export value.

These continuous exporters were able to continue exporting during 2020, in the face of COVID-19 challenges. To some extent, this fact already reflects their resilience. Compared to the rest of the exporter population, they were likely to: (a) be medium to large sized businesses; (b) export frequently each year (lodge a larger number of export declarations); and (c) have more diversified export markets (export to a larger number of countries).

A sub-group of these continuous exporters was then further categorised as “resilient” – which we define as those continuous exporters who achieved total export sales in 2020 that met or exceeded their average annual export sales over 2016-2019.  These resilient exporters were least impacted by the COVID-19 pandemic. We observed that: (a) large or medium businesses had a higher proportion of resilient exporters than small businesses; and (b) exporters with greater market diversification (exporting to more countries) were more likely to be resilient than exporters with single market.

The analysis in this paper indicates possible directions for future research.

One direction for future research is to link both import and export declarations to BLADE entities, in the same knowledge graph. This would then allow the researcher to, for example, analyse how international supply chain disruptions may have impacted Australian exporters, as a substantial proportion of exporters source their inputs from imports.

The performance of the continuous exporters can also be analysed by estimating their growth distributions. For example, preliminary estimates of the log growth of exports, using kernel density estimation, depart from a normal distribution. This seems to be consistent with findings in the literature on the firm growth distribution (Bottazzi and Secchi 2006, Arata 2018) and is worth investigating further. Although the drivers of export growth may differ for individual businesses, the firm growth distributions could provide insights into statistical properties of underlying growth processes.

Given that a substantial proportion of exporters may operate intermittently, it is worth extending the growth performance analysis to these intermittent exporters (van den Berg et al. 2020).

Another direction for future research would be to apply time series clustering methods to analyse time series patterns of export value or quantity (categorised by destination country, commodity lines, industry, exporter’s main state of operation, etc.) and then link those patterns to exporter characteristics. This approach may provide further insights into the challenges that exporters in different industries have been facing and the business strategies and characteristics that have been adopted by the resilient exporters.

Finally, there would also be considerable benefit in linking business location data to the knowledge graphs, to look for geospatial patterns in exporter and importer characteristics. For example, researchers could study how Australian importers and exporters are being impacted by, and responding to, localised natural disasters, such as flooding or bushfires.

Qinghuan Luo and Tim Cadogan-Cowper (Methodology Division)²⁰