The summary statistics of Cambodian industrial structure, 2005–2015
This section describes the industrial structure base on IOT of the years 2005, 2010, and 2015, as presented in Table 2. Cambodia’s economy depended on the agriculture sector, which accounted for 30% of total gross output in 2005 and then fell to 29% in 2015. It was the highest contributor to overall GDP and value-added, but relatively lost its share to the manufacturing and service sectors. During 2005–2015, five economic sectors (namely, food and beverage, transportation and communication, textile, other manufacturing, and tourism sector) were the dominant sector contributing to the total gross output and GDP. These sectors were also the top ranking in terms of providing a significant share to value-added. Meanwhile, all sub-service sectors' stock to gross output and GDP, except tourism, have soared over observed periods. Oppositely, these sectors were nearly constant growth contributing to value-added.
The export and import structure of Cambodia is displayed in Table 3. Cambodia mainly exports agricultural, textile, other manufacturing, and transportation and communication items. These four categories accounted for 84% of total exports in 2005 and decreased to 79% in 2015. This trend favored the service sector, which made up 9.7% in 2005, and 14% in 2015. The tourism sector represented the third-largest share of total exports in the service sector after the wholesale and retail industry. The sector’s export intensity is defined as the ratio of each sector’s export to domestic production. In 2005, the textile industry was the most export-intense industry, which exported 59% of its outputs to foreign markets. It is followed by agriculture (46%), other manufacturing (41%), and the food and beverage industry (25%). In 2010, the textile, other manufacturing, and transportation and communication industries showed the top three most export-intense sectors, approximately 49%, 43%, and 38.5%, respectively. These industries were ahead of the food and beverage (21%) and the tourism industry (15.5%). In 2015, the transportation and communication sector was the second most export-intense, followed by the other manufacturing (37%), mining and quarry (31%), agricultural (24%), and tourism industry (22.1%). The export intensity of the tourism sector has surged from 13.1% in 2005 to 22.1% in 2015. This increasing trend pinpoints that Cambodia’s tourism industry highly depends on the growth of international tourism demand. It is also the main service export, which possibly generates a considerable amount of export-earning. Regarding imports, Cambodia highly imports other manufacturing, textile, wholesale and retail, and transportation and communication items, exhibiting 92% of total imports in 2005 before decreasing to 85% in 2015. The share of tourism import to total import has surged from 0.8% in 2005 to 5% in 2015. As shown in Table 3, the import intensity of the tourism sector has surged from 3.5% in 2005 to 21.2% in 2015, indicating high economic leakages in this industry. The reasons could be that there was high demand for standard tourism goods and services, increasing the tour packages between Cambodia and its neighboring countries (Thailand and Vietnam), no direct flight between Cambodia and long-haul tourists (Europe and USA), and an increasingly international connecting flight between Cambodia with China and India.
Furthermore, Table 4 shows the structure of labor income and labor intensity of each sector. The agriculture and other manufacturing industry were the highest contributions to total labor income for all 3 years but with a relatively downward trend. Between 2010 and 2015, the top three service sectors (i.e., tourism, wholesale and retail, and transportation and communication) were a significant contributor to the total labor income. These sectors imply the importance of service industries concerning contribution to net value-added. The labor income intensity of each sector is also included in Table 4. It is the fraction of labor income to total domestic production. Two service sectors (public administration and education) were the most labor income-intense industry for all 3 years. It is followed by the tourism industry, which displayed an increasing trend from 27% in 2005 to 34% in 2015. This sector indicates that it potentially generates employment and labor income earning.
Backward and forward linkage analysis
This section illustrates, in Table 5, the result of the Hirschman–Rasmussen BL and FL indices during 2005–2015. The BL is also called the intensity of intermediate inputs. It indicates that a sector demands inputs from other industries for its production. The BL of sector j quantifies the change in economy-wide income relative to the average change in the economy caused by a unitary injection in the final demand of sector j. If the BL is more than one, it implies that a unit change in the final demand sector will increase activities in the whole economy (Otchia 2013). The FL shows an economic activity that supplies intermediate inputs to other sectors and final domestic demand. The FL of sector j quantifies the change in income in sector j, relative to the average change in the economy, caused by a unitary injection in the final demand of all sectors. If the FL for sector j is more than one, sector j’s income is higher than the average income change in the economy after a unitary injection in all sectors (Otchia 2013). The linkages of each sector have been measured using the PyIO 2.1, a module for IO analysis developed by researchers at the University of Illinois’ Regional Economic Applications Laboratory. It is a general-purpose, open-source computer programming language writing in Python.
The analysis finds that 6 out of 15 sectors (namely, food and beverage, other manufacturing, construction, textile, transportation and communication, electricity, and) have relatively had strong backward linkage with the value of greater than one in the three-point periods. These sectors point out that these industries are input dependent on other economic sectors, showing a significant and positive impact on the nationwide economy. Diversely, the rest of the sectors have shown weak backward linkage. Most service sectors (e.g., wholesale and retail, financial and insurance, real estate, public administration, education, and human health) exhibit low backward linkage. It argues that these industries make relatively less intermediate inputs demand from other economic sectors. The agricultural and mining and quarrying sectors have resulted in a low backward linkage, implying that both sectors have a relatively small degree of input dependence on other industries in the economy. The textile, other manufacturing, construction, transportation and communication, and wholesale and retail registered as the top five highest forward linkages across periods. These sectors imply an essential role in supplying inputs to other economic segments. The tourism sector showed a strong forward linkage in 2010 and 2015. The reason could be because of the impact of tourism law and 10-year national tourism strategic development plan (2012–2020) implementation in 2009 and 2011, respectively, that encouraged the private sectors to develop tourism products, increase travel facilitation, develop domestic infrastructure, enhance regional and global connectivity, and diversify tourism destinations. These initiatives lead to an increase in the domestic linkage between tourism and other sectors in the economy. This result is in line with the studies by Beynon et al. (2009), Khanal et al. (2014), and Munjal (2013), who find tourism forward linkage greater than one in the case of the UK’s economy, Lao PDR’s economy, and India’s economy, respectively. In contrast, most service sectors have low forward linkage, exhibiting that these industries are relatively small supply inputs to other economic sectors.
Concerning the linkage trend, the tourism sector has decreased backward linkage overtime periods. This sector pinpoints that this sector is relative to demand intermediate inputs from its sector or sub-related sectors. On the contrary, the tourism sector has increased its forward linkage across times, implying that this sector supplies inputs to other economies via the business travel sector. The strong tourism forward linkage may generate high backward linkage in its related industries. It is in line with the construction, wholesale and retail, and transportation and communication, showing a stable and robust growth of backward linkage. Also, the increasing trend of the forward linkage in both the transport and communication and tourism sectors indicates the importance of these sectors in supplying intermediate inputs to tourism-related sectors and other sectors in the national economy. This finding is consistent with Khanal et al. (2014).
Key sector analysis
The key sector analysis is used to cluster segments into four types: key sectors, forward-oriented sectors, backward-oriented sectors, and weak sectors. This classification is based on normalizing backward-and-forward linkage indices, clearly explained in Sect. 4.1. The observed economic sectors have been categorized into four quadrants, shown in Figs. 2, 3 and 4. The upper right-and-left quadrants are, respectively, key sectors and forward-oriented sectors. The lower right-and-left quadrants are backward-oriented sectors and weak sectors, respectively.
We find that textile, other manufacturing, and transportation and communication sectors are key sectors that have backward and forward linkages higher than one. The tourism sector shifted to a key sector in 2010 and 2015. This sector means that a surging investment or productivity these sectors provide a spillover impact on other industries. The backward-oriented sectors are across 3 years, namely, the food and beverage, electricity, and construction sector. The mining and quarrying sector became a backward-oriented sector in 2015. It indicates that an increase in these sectors’ production provides more input demand from other industries. The wholesale and retail sector is continuously a forward-oriented sector across periods. Agriculture became into the forward-oriented sectors in 2010 and 2015. This sector implies that these industries’ outputs have been used as inputs for other’s industrial production. Moreover, there has been seen that most sectors are weak-oriented sectors during the 3 years.
The landscape of the Cambodian economy
Figures 5, 6 and 7 illustrate the Cambodian economic landscape for 3 years (2005, 2010, and 2015). The graph shows the relationship between structural industries through the hierarchy of forward-and-backward linkage.
In 2005, the landscape economy presented a considerable variation of inter-sectoral linkages, implying a low inter-industry linkage among sectors. The hierarchy of the highest bar was the intersection between the food and beverage and textile sector. This conjunction indicates that industrialization played an essential role in Cambodia’s economy. The third and four apexes were at the interconnection of economic sectors 8–9 (wholesale and retail–construction) and 3–7 (textile–transportation and communication). This link pinpoints that the manufacturing and service sectors become active in the economy. Also, the sixth and seventh apexes showed the intersection of industries 6–15 (electricity–tourism) and 15–4 (tourism–food and beverage). These sectors have similar heights, indicating that the tourism, electricity, and food and beverage sectors have a strong inter-link with other industries in the economy.
Figure 6 shows Cambodia’s economic landscape in 2010. The highest bar is the junction of sectors 5–3 (other manufacturing–textile), and the second apex is the intersection of industry 4 (food and beverage) and 5 (other manufacture). This linkage reflects that the process of industrialization in Cambodia’s economy remains essential for the economic development in Cambodia. The third and four apexes interact with sectors 8–9 (wholesale and retail–construction) and 3–7 (textile–transportation and communication). This interaction presents an active role of sectors in the economy. Also, the sixth and seventh apexes are at the junction of the industry 6–15 (electricity–tourism) and 15–4 (tourism–food and beverage). The height of these sectors has relatively more variation than in 2005, presenting a low association between tourism, electricity, and food and beverage. Thus, there is a shortage of domestic products supplied to the tourism sector when tourism expands. The economic landscape of Cambodia in 2010 shows a considerable variation in inter-industry linkages.
Similarly, Fig. 7 exhibits the Cambodia economic landscape in 2015. The highest bar is the junction of sector 5 (other manufacturing) and itself. It is followed by the intersection of industry 4–3 (food and beverage–textile). The third and four apexes are at the inter-link of sectors 8–7 (construction–transportation and communication) and 3–9 (textile–wholesale and retail), followed by the fifth apex of the inter-industry linkage between industry 7 (transportation and communication) and sector 1 (agriculture). This interaction indicates that agriculture, other manufacturing, and service sector are actively economic performance in the economy. Also, the association between tourism and other economic sectors did not change in 2015. The economic landscape of Cambodia in 2015 shows a significant variation in inter-industry linkages.
Field of influence
I use the field of influence approach to further investigate the sectors’ interdependences for the years 2005, 2010, and 2015, in addition to the linkage analysis and economic landscape. This approach extends the conventional key sector analysis and economic landscape by defining the combination of key sectors that have the most significant contribution to economy-wide output. According to Otchia (2013), this approach is essential to define sectors where policy intervention will create the most significant volume change in Cambodia’s economy. As can be seen in Fig. 8, each productive linkage is highlighted as the color scales. The blank box and lighter colors note the value of coefficients below the mean and above mean plus a standard deviation, respectively—the intermediate color marks between one and two standard deviations. The darker blue color marks the above two standard deviations—the result presented in Fig. 8. Three industries, namely, textile (sector 3), other manufacturing (sector 5), and transportation and communication (sector 7), reveal the most significant coefficient of the field of influence of changes during the 3 years. These sectors present more importance in the economy. At the same time, the rest of the industries have relatively lost the critical coefficient of Field of Influence over the examined periods.
In terms of linkages, the agriculture sector has intensively interconnected (above two standard deviations) with the textile sector in 2015 and intermediated linkage in the rest of the 2 years. The textile industry has integrated into the production process within the industry itself and the most robust strength linkage (above average plus two standard deviations) with other manufacturing, and transportation and communication. Interestingly, the wholesale and retail sector presents the most substantial ties above average plus two standard deviations with the textile sector in 2005 and 2010, but less intensity in 2015. During the three periods, the tourism sector shows the most robust strength linkage (between one to two standard deviations) with textile (sector 3) and between mean to one standard deviation for the other manufacturing (sector 5) and transportation and communication (sector 7). Surprisingly, the tourism sector is relatively lost linkage with the agriculture (sector 1), food and beverage (sector 4), and wholesale and retail (sector 9), indicating weak domestic linkages among these sectors causing high economic leakages through high demand for imported goods.