NC State
Komut, O. (2022). "The economic impacts of Covid-19 on the forestry sector: A case study in Turkey," BioResources 17(3), 4030-4042.


The Covid 19 pandemic has led to considerable destruction of social and economic areas at a global level. This study aims to determine the economic impact of the Covid 19 pandemic on the Turkish forestry sector. In this context, 5 years (from 2017 to 2021) of wood-based product sales of an administrative unit, which carries out regional forestry activities in Turkey, were studied. The data concerning the product groups were subjected to a Laspeyres price index analysis based on the base period weight through the price and estimated price increase rate variables. In addition, correlation analysis was utilized to determine the relationships between the determined variables. The findings showed that the Covid 19 pandemic led to decreases in the Laspeyres price index values for the price and estimated price increase rates when compared with the pre-pandemic period, which was different on a product group’s basis. As a result, it can be said that the Covid 19 pandemic process created a considerable potential for a loss of income in wood-based products, which is one of the primary outputs of the forestry sector, and as of 2021, a recovery process has started.

Download PDF

Full Article

The Economic Impacts of Covid-19 on the Forestry Sector: A Case Study in Turkey

Osman Komut *

The Covid 19 pandemic has led to considerable destruction of social and economic areas at a global level. This study aims to determine the economic impact of the Covid 19 pandemic on the Turkish forestry sector. In this context, 5 years (from 2017 to 2021) of wood-based product sales of an administrative unit, which carries out regional forestry activities in Turkey, were studied. The data concerning the product groups were subjected to a Laspeyres price index analysis based on the base period weight through the price and estimated price increase rate variables. In addition, correlation analysis was utilized to determine the relationships between the determined variables. The findings showed that the Covid 19 pandemic led to decreases in the Laspeyres price index values for the price and estimated price increase rates when compared with the pre-pandemic period, which was different on a product group’s basis. As a result, it can be said that the Covid 19 pandemic process created a considerable potential for a loss of income in wood-based products, which is one of the primary outputs of the forestry sector, and as of 2021, a recovery process has started.

DOI: 10.15376/biores.17.3.4030-4042

Keywords: Forestry sector; Laspeyres index; Covid-19; Economic impacts

Contact information: Gümüşhane University, Department of Forestry and Environment Sciences, Institute of Natural Applied Science, Gümüşhane 29000 Turkey; * Email:


The forestry sector can be defined as a broad concept which is comprised of forest products industry management as well as forest resource management and other subsidiary forestry activities (Hajdúchová et al. 2012; European Commission 2013). Therefore, forest resources have a major economic potential with their indirect and direct usage values (Shackletona et al. 2007). In addition, industrial activity areas associated with forests play an essential role in rural development (Kara et al. 2019; Griffin et al. 2020). The forestry sector plays a considerable role in the raw material procurement for the forest products industry, due to its high forward connectivity rate (Kara et al. 2019; Türker 2020). The most important source of income for forestry managements is logs sale, which forms more than 78% of the total sales (Sujová et al. 2017). For fuelwood, the variability in demand also makes the total volume and income level of this product a variable (Parobek et al. 2014). In addition, it is reported that the financial value of the timber stock is taken into account from the traditional point of view for the evaluation of tropical forests (Mahapatraa and Tewarib 2005).

While approximately 0.2% of the forest areas in Turkey are privately owned, the rest of it is fully managed by the General Directorate of Forestry (GDF) under state ownership (Kara et al. 2019; GDF 2021a). The GDF uses the auction method for the marketing of forest products according to the Forestry Law 6831 (Türker 2020). As of 2020, the total planted tree stock in Turkey is 1,697,055,000 m3 (GDF 2021a). In addition, the annual wood consumption is 32 million m3 in the country. While approximately 26.3 million m3 of the total consumption amount is addressed by the GDF, 5 million m³ is supplied by the private sector and 1.5 million m³ to 2 million m³ is supplied through imports (GDF 2021b). Within the scope of private sector production, there are special forests, title deed cuts made from places that are not considered forests because they are smaller than 3 ha, and productions made from fast-growing species plantations in agricultural areas (Kök 2009). As such, the GDF is in the position of being the most crucial supplier of the forest products industry (Gültekin et al. 2021). While the industrial wood production of GDF was 17,009,998 m3 in 2016, it reached 24,751,066 m3 in 2020 (GDF 2020). Despite an increase of approximately 46% in the industrial wood supply of GDF compared to 2016, there is still a supply gap in the sector (Ministry of Development 2014; Akkaya et al. 2020). In a further breakdown, 40% (9,790,637 m3) of the total annual industrial wood production of GDF is logs, 37% is fiber chip wood (9,105,038 m3), and 33% (9,799,742 m3) is other industrial wood types. The total annual fuelwood production is 4,047,510 m3 (GDF 2020).

Covid-19, which emerged from the city of Wuhan in China and has spread to the world, was declared as a global epidemic on March 11, 2020 (Sen and Singer 2020). With the emergence of Covid-19, economies and sources of income have been cut (Hilsenroth et al. 2021; Saxena et al. 2021). A dependence on certain services and products, including forest resources, has emerged (Hilsenroth et al. 2021). During the pandemic period, implementations have been carried out in order to restrict economic activities in many countries around the world (Zaremba et al. 2020; Zhang et al. 2020; Dong et al. 2021). In contrast with the restrictions in urban areas, a considerable increase has been observed in the demand for recreational services concerning forest resources (Derks et al. 2020). The US Fish and Wildlife Service reported that hunting licenses have increased by 8.2% during the pandemic period. The importance of forestry services makes measuring possible changes in Covid-19 necessary (Hilsenroth et al. 2021). In addition, it is reported that during the Covid-19 pandemic process, restrictions such as curfews negatively affect field work on research and development in the field of forestry (Bhandari et al. 2021).

In Turkey, the Covid-19 pandemic has led to critical problems in the economic system as well as disruptions in labor markets and commercial activities (UN Turkey 2020). Micro and small-sized enterprises were more negatively affected by the process when compared with medium and large-sized enterprises. Activities have come to a halt in 35% of micro enterprises and in 24% of small enterprises (UN Turkey 2020). In a similar manner, the forest products industry sector was negatively affected by the process. The priority issue for the new possible negative processes of the sector is raw material procurement (Bayram 2021). However, the first studies on the subject have shown that not every business in the sector is affected by the process in the same manner (Yücel and Durak 2021).

This study aims to reveal the economic effects of the Covid-19 pandemic on the Turkish forestry sector, based on wood-based products, in terms of sales amount and income level. The algorithm of the study is designed to obtain general inferences for the forestry sector, based on the economic activities of the unit selected as an example.



The Amasya Regional Directorate of Forestry (RDF), which is affiliated with the GDF in Turkey, was chosen as the study area (Fig. 1). In the selection of the sample area, the following parameters were used: (1) the presence of a high-capacity industrial management which processes fiber chip wood within its area of responsibility; and (2) the RDF with the largest forest assets (Komut and Santo 2020; GDF 2021a). A forest industry facility with an annual processing capacity of approximately 56,000 m3 of fiber and chip wood is located in the region (Doğan and Akyıldız 2017). The total number of enterprises processing wood-based products in the Amasya RDF region is 1,386 (including forestry and logging industry, furniture industry, paper products manufacturing industry and other wood and wood products industry) (SSI 2020). The Black Sea Region, where the Amasya RDF is located, is the geographical region that contains the largest part (24.4%) of the forest assets of the country with 5,593,342 ha (GDF 2021a). Amasya RDF has the highest forest area (27%) in its geographical region, with 1,529,275 ha of forest area (GDF 2021a).

Fig. 1. The location of the study area (GDF 2021c)


Data collection

The study data consists of the official sales data of wood-based product groups in a 5-year period between 2017 to 2021 of the selected sample unit (GDF 2021d). The time period of the research data was determined to cover the Covid-19 pandemic period, based on similar studies (Dikilitaş and Öztürk 2010; Coşgun 2017; Komut and Santo 2020). The sales data was analyzed by classifying based on the algorithm shown in Fig. 2. Under the title of log product class, all log batches in all diameter and length classes in the quality class 1, 2, and 3 were included in the analysis. The tree species discussed within the scope of the research were handled for two different sales methods: stumpage sales and traditional warehouse sales.

Fig. 2. Research data classification algorithm

Analysis of data

The price index is considered as an indicator of the average price movement of fixed goods and services baskets over time (Sivaram and Sandeep 2010; Tosovska 2010). In addition to the Paasche price index and the Fisher price index, one of the most widely used indexes is the Laspeyres price index, which utilizes the base period weight (Hlavackova et al. 2015). These indexes are used to compare changes in the weighted price and quantity over a time period and they require the reference year to be used throughout the analysis (Önder and Konuk 2018). In this study, the Laspeyre’s price index (LPI) based on weighting was used in the analysis of the data due to the significant differences between the sales volumes of the product groups. The LPI index was calculated with Eq. 1,


where P1i is the period price given for the ith product (₺/m3), P0i is the basic period price of the ith product (₺/m3), and Q0i is the basic period weight of the ith product (Ahn 2005; Hlavackova et al. 2015; Önder and Konuk 2018).

The product basic circuit weight was calculated using Eq. 2,


where Qi is the sales amount of the ith product.

The determination of the appraised value, the discount/upgrade rates that can be made in these prices are determined by GDF on the basis of product costs (Türker 2020). The change between the appraised value (AV) for batches of wood products offered for sale and the price formed as a result of the auction was calculated with Eq. 3,

ARri=(Pi-AV)/AV (3)

where ARri is the rate of increase in an appraised value (%), Pi is the sales price (₺/m3), and AV is the appraised value (₺/m3) (Öztürk et al. 2008; Komut et al. 2013).

A correlation analysis was performed to determine the relationships between the year, wood species, sales price, and ARri variables in the 5-year period between 2017 and 2021(Kalaycı 2010). In this context, SPSS statistical analysis software (version 20, IBM Corp., Armonk, NY) was utilized. The calculations and graphical presentations concerning the data were made in Microsoft Office Excel 2013.


The changes in the AV values of the wood products handled within the scope of the study were determined for each calculated year compared to the previous year. For the 5-year period between 2017 and 2021, the annual ARri average was 24% for the log product group, 15% for fiber chip wood, 14% for fuelwood, and 21% for stumpage sales (GDF 2021d). Sales prices for the product batches will be higher than the AV, regardless of different conditions (Öztürk et al. 2019). Therefore, in this study, the price-based LPI index values were analyzed through support with the ARri-based LPI index values.

Table 1 shows the distribution of the wood-based products sold in the 1st, 2nd, and 3rd quality classes of the Amasya GDF, a part of the Turkey GDF, between 2017 and 2021, according to the wood type. The total amount of industrial wood sales, which started to increase as of 2020, reached the highest value of 248,950 m3 in 2021 (as shown in Table 1).

Table 1. The 5-Year Industrial Wood (1st, 2nd, and 3rd Quality Class) Sales Quantities according to Tree Species in Amasya RDF (GDF 2020; GDF 2021b)

The data obtained from the fiber chip wood, log, fuelwood, and stumpage sales implementations, and the data obtained from the ARri values occurring from the AV between the years 2017 and 2021 can be seen in Fig. 3. In 2019, it was determined that there were decreases in the ARri for coniferous tree (CT) and broad-leaved tree (BLT) batches in fiber chip wood, fuelwood, and stumpage sales (Fig. 3). An upward tendency in the ARri values again has been observed for these product groups since 2020. The decrease in the ARri for log products, which is the most important output of the forestry sector for wood-based product groups was found to have considerably decreased in 2020. However, the ARri values in this product group considerably increased in 2021 (as shown in Fig. 3). This situation can be seen as an important indicator of the economic recovery that started with the end of 2020 (Hilsenroth et al. 2021; Riddle 2021; UNECE/FAO 2021). However, in this process, the community vaccination rate and the re-emergence of the virus will have a major impact on the pace of the economic recovery process (Hardcastle and Zabel 2021). Average AR and Pi values of product groups in Amasya RDF for the years 2017-2021 are given in Table 2.

Table 2. Average ARri and Pi values of product groups in Amasya RDF in 2017-2021 (GDF 2020; GDF 2021b)

Table 3 shows the LPI calculated through the prices of log, fiber chip wood, fuelwood and stumpage sales and ARri values between 2017 and 2021. LPI values are calculated by considering the years 2017, 2018, 2019 and 2020 are as the reference year for each product group in the table.

Fig. 3. Product group comparisons according to the ARri: (a) Fiber chip wood; (b) Fuelwood; (c) Logs; and (d) Stumpage sales

The reference year 2017 and the price based LPI values show a price increase of 37% for the log product group in 2020. However, the ARri -based LPI index values for the same period indicate a 30% decrease in the ARri. A similar relationship is also valid for the LPI index values with reference year 2018. Similarly, while the LPI price index for the fuelwood product group showed an increase of 18% for 2020 when compared with 2017, the LPI ARri index showed a decrease of 28%. In the stumpage product group, similar results were obtained for both indexes in terms of the decrease/increase direction and index values of the LPI price and LPI ARri index values for the reference years, unlike other product groups (as shown in Table 3). Considerable increases were observed in the 2021 LPI price and LPI ARri index values for all product groups (as shown in Table 3, Fig. 3, and Fig. 4).

Table 3. 5-Year Sale Price of Product Groups and ARri -based Laspeyres Index Values

This case can be explained with the reduction in Covid 19 restrictions as of 2021 and the re-activation of economic activities. However, it is known that some of the price differences that occur over the years are due to the AV (Türker, 2020). An increase in log prices has been predicted to occur during Covid 19 in the USA and an increase is also predicted in the production amount depending on this increase in the continuation of the process (Timber Mart-South 2021). The 36% increase in the total production amount in Amasya RDF in 2021 compared to the previous year (Table 1) and the 217% increase in the LPI index in the timber product group (Table 3) indicate similar results. Differentiations have been reported for the influence of Covid 19 for forest products sub-sectors (ILO 2020; Størdal et al. 2021). Therefore, it can be said that the results in the same direction were obtained for the 4 primary product groups selected for this study. In the timber industry, there has been a decrease in demand during the Covid 19 period, and there has been a decrease in the supply prices of raw materials for the market (Riddle 2021). Similar declines in demand for wood products have been reported in China (Chen and Yang 2021). On the other hand, it can be said that the increase in logging prices in 2021 is a reflection of the increasing demand in sectors related to forest runes (Stanturf and Mansuy 2021).

As of the end of 2020, the recovery process in the sector has begun, and the record price formations were observed in some economic product groups (Hilsenroth et al. 2021; Riddle 2021; UNECE/FAO 2021).

The LPI price index values, which were calculated based on 2018, have shown that the increases in prices remained limited in 2020, when restrictions occurred during the Covid-19 period. However, the LPI ARri index of all the product groups have shown that the ARris considerably decreased in 2020 when compared with 2018 (as shown in Fig. 4). The findings imply considerable income losses in 2020 for the forestry organization, which is the most important raw material supplier for the Turkish forest products industry (Gültekin et al. 2009).

It has been determined that this income loss is at the level of 28% for log, 1% for fiber chip wood and 6% for stumpage sales, according to the average of years excluding the Covid-19 pandemic period (Table 2). Ratnasingam et al. (2020) reported that the furniture industry in Malaysia, which largely falls into the small and medium-sized business classes, has been critically affected by the supply chain inconveniences occurring because of the restrictions during the Covid 19 pandemic.

In the Turkish domestic markets, sales have decreased by 30% due to the Covid-19 restrictions and problems that occurred in the supply of wood-based forest products raw materials (Bayram 2021). In the continuation of the process, it is foreseen that the uncertainty in the supply and demand in the markets will persevere (Ozenc 2020).

Fig. 4. The Covid-19 period and the: LPI price (a); and LPI ARri indexes (b)

Correlation analysis is used to test the linear relationship between two variables and to determine the degree of the relationship (Kalaycı 2010). A strong and positive correlation was detected between the sales year and the sales price in the log product group, which was affected most during the Covid 19 pandemic period.

A weak and positive correlation was detected between the wood species (CT/BLT) and the sales price. In addition, it was comprehended that there was a strong positive correlation between the sales price and the ARri (Table 4). These findings showed that the sales price increased with increasing years and accordingly ARri tended to increase. A similar relationship was also emphasized in previous studies (Öztürk et al. 2011).

Table 4. The Results of the Correlation Analysis between the Variables Determined for the Log Product Group


  1. During the Covid 19 pandemic process, there was no significant potential loss of income regarding the products offered to the market with the application of stumpage sales in the forestry sector. On the other hand, potential income decreased in wood products offered to the market with warehouse sales.
  2. In the forestry sector during the Covid 19 pandemic, among the log, fiber chip, and fuelwood product groups offered to the market within the scope of warehouse sales, the log group, which is the most important wood product output of the sector, was the product that was most adversely affected.
  3. The resumption of economic activities at the end of 2020, when the Covid 19 restrictions started to be lifted, led to considerable income increases in the forestry sector as of 2021. However, the variability in the demand for the forestry sector outputs for the last 5 years and the concerns about the development of the pandemic creates uncertainty.
  4. The changes in the demand for wood-based product outputs of the forestry sector during the Covid 19 pandemic process have led to considerable economic losses in the sector.


I would like to thank Amasya Regional Directorate of Forestry for their assistance in obtaining the research data.


Ahn, S. (2005). “Comparisons of index numbers: An application to sawmills and planing mills industry of U.S.,” Journal of Korean Society of Forest Science 94(2), 82-89.

Akkaya, M., Ok, K., Koç, M., Akseki, İ., and Akkaş, M. E. (2020). “Sectoral use of imported wood raw material in Turkey,” Turkish Journal of Forestry 21(3), 279-293. DOI: 10.18182/tjf.766501

Bayram, B. C. (2021). “The impact of COVID-19 on Turkish forest products industry,” Journal of Bartin Faculty of Forestry 23(2), 565-570. DOI: 10.24011/barofd.897343

Bhandari, M. S., Pandey, S., Dabral, A., Meena, R. K., and Kant, R. (2021). “Global forestry perspective: COVID-19 impact and assessment,” Natl. Acad. Sci. Lett. 44(6), 571–574. DOI: 10.1007/s40009-021-01062-x

Chen, J., and Yang, C.-C. (2021). “The impact of the COVID-19 pandemic on consumers’ preferences for wood furniture: An accounting perspective,” Forests 12(12), 1637. DOI: 10.3390/f12121637

Coşgun, U. (2017). “Evaluation of production and marketing in beech (Fagus orientalis Lipsky) Forests,” in: Proceedings of the 4th National Forestry Congress, 15-16 November, Antalya, Turkey, pp. 156-169.

Derks, J., Giessen, L., and Winkel, G. (2020). “COVID-19-induced visitor boom reveals importance of forests as critical infrastructure,” Forest Policy Economics 118, 1-5. DOI: 10.1016/j.forpol.2020.102253

Dikilitaş, K., and Öztürk, A. (2010). “Examination of the last five years’ auction sales of Artvin Regional Directorate of Forestry,” in: Proceedings of the 3rd National Black Sea Forestry Congress, 20-22 May, Artvin, Turkey, pp. 259-269.

Doğan, K., and Akyıldız M. H. (2017). “Situation of wood-based panel industry in Turkey,” Pro Ligno 13(4), 617-629.

Dong, X., Song, L., and Yoon, S.-M. (2021). “How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?” The North American Journal of Economics and Finance 58, 1-14. DOI: 10.1016/j.najef.2021.101546

European Commission (2013). “A new EU forest strategy: For forests and the forest-based sector (SWD (2013) 343 final),” ( cellar: 21b27c38-21fb-11e3-8d1c-01aa75ed71a1.0022.01/DOC_1&format=PDF), accessed on 26th December 2021.

GDF (2020). “Forestry statistics 2020,” (, accessed on 25th December 2021.

GDF (2021a). 2020 Turkey Forest Presence, T. C. Ministry of Agriculture and Forestry General Directorate of Forestry Publications, Ankara, Turkey.

GDF (2021b). General Directorate of Forestry Performance Program for 2021, GDF Strategy Development Department, Ankara, Turkey.

GDF (2021c). “Forestry forest map,” (, accessed on 1st January 2022.

GDF (2021d). “Wood based forestry product tenders​,” (, accessed on 25th December 2021.

Griffin, J., Seale, R., Owens, F., and Grace, L. (2020). “Construction of an economic model for prospective forest products manufacturing facilities,” BioResources 15(2), 3874-3887. DOI: 10.15376/biores.15.2.3874-3887

Gültekin, Y. S., Kayacan, B., and Bentler, P. M. (2021). “Determination of stakeholders’ perception of stumpage sales policy in forest management directorate: a case study from western black sea region of Turkey,” Fresenius Environmental Bulletin 30(1), 135-147.

Gültekin, Y. S., Kayacan, B., and Ok, K. (2009). “An investigation on timber demand of forest industry in Düzce province,” Duzce University Journal of Forestry 5(2), 75-94.

Hajdúchová, I., Sedliačiková, M., Halaj, D., Krištofík, P., Musa, H., and Viszlai, I. (2016). “The Slovakian forest-based sector in the context of globalization,” BioResources 11(2), 4808-4820. DOI: 10.15376/biores.11.2.4808-4820

Hardcastle, P., and Zabel, A. (2021). “Initial assessment of the impact of COVID-19 on sustainable forest management Western European and other States,” (, accessed on 6th January 2022.

Hilsenroth, J., Grogan, K. A., Crandall, A. M., Bond, L., and Sharp, M. (2021). “The impact of COVID-19 on management of non-industrial private forests in the Southeastern United States,” Trees, Forests and People 6, 1-8. DOI: 10.1016/j.tfp.2021.100159

Hlavackova, P., Brezina, D., and Sujova, A. (2015). “The price formation of raw wood in the Czech Republic and a comparison with the neighbor states,” Procedia Economics and Finance 26, 389-395. DOI: 10.1016/S2212-5671(15)00869-2

ILO (2020). “Impact of COVID‐19 on the forest sector,” (–en/index.htm), accessed on 20th December 2021.

Kalaycı, Ş. (2010). SPSS Applied Multivariate Statistics Techniques, Asil Publication Distribution, Ankara, Turkey.

Kara, O., Şahin, Ö., Bekar, İ., and Kayacan, B. (2019). “International competitiveness analysis of industrial wood and wood products sector: The case of Turkey,” The International Journal of Economic and Social Research 15(1), 15-32.

Komut, O., and Santo, S. (2020). “Change of income from forest products based on geographical location of enterprises and some marketing variables,” Gümüşhane University Journal of Science Institute 10(3), 724-732. DOI: 10.17714/gumusfenbil.717281

Komut, O., İmamoğlu, S., and Öztürk, A. (2013). “Blue stain degradation on the Scots pine log and its effect on the sale price,” Artvin Coruh University Journal of Forestry Faculty 14(2), 283-291.

Kök, G. (2009). “Forest products supply demand relations in the world and in Turkey,” in: Proceedings of the II. Congress of Socio-Economic Issues in Forestry, 19-21 February, Isparta, Turkey, pp. 349-360.

Mahapatraa, A. K., and Tewarib, D. D. (2005). “Importance of non-timber forest products in the economic valuation of dry deciduous forests of India,” Forest Policy and Economics 7(3), 455-467. DOI: 10.1016/j.forpol.2004.02.002

Ministry of Development (2014). Sustainable Forest Management Specialization Commission Report, Tenth Development Plan, Ankara, Turkey.

Önder, S., and Konuk, A. (2018). “Total productivity and profitability analyses of Turkish boron mining,” The Journal of Engineering and Architecture Faculty of Eskisehir Osmangazi University 26(3), 107-116. DOI: 10.31796/ogummf.404467

Ozenc, F. K. (2020). “An assessment of the impact and possible consequences of the pandemic on the functioning of global supply chains,” in: Economic, Social and Political Impacts of the COVID-19 Pandemic, Istanbul University Publishing House, Istanbul, Turkey, pp. 69-86.

Öztürk, A, Kayacan, B., and Dikilitaş, K. (2008). “Effect of bark beetles on timber sales: A preliminary study in Artvin Regional Forest Directorate,” Journal of DOA 14, 119-130.

Öztürk, A., Kayacan, B., and Dikilitaş, K. (2011). “A linear price model for insect-damaged industrial roundwood: A case study in Northeastern Turkey,” African Journal of Business Management 5(21), 8552-8557. DOI: 10.5897/AJBM11.1016

Öztürk, A., Demirci, U., and Dikilitaş, K. (2019). “Effect of production year on log sale prices: Example in Artvin, Turkey,” Kastamonu University Journal of Forestry Faculty 19(3), 342-349. DOI: 10.17475/kastorman.662726

Parobek, J., Paluš, H., Kaputa, V., and Šupín, M. (2014). “Analysis of wood flows in Slovakia,” BioResources 9(4), 6453-6462. DOI: 10.15376/biores.9.4.6453-6462

Ratnasingam, J., Khoo, A., Jegathesan, N., Wei, L. C., Latib, H. A., Thanasegaran, G., Liat, L. C., Yi, L. Y., Othman, K., and Amir, M. (2020). “How are small and medium enterprises in Malaysia’s furniture industry coping with COVID-19 pandemic? Early evidences from a survey and recommendations for policymakers,” BioResources 15(3), 5951-5964. DOI: 10.15376/biores.8.3.5951-5964

Riddle, A. A. (2021). “COVID-19 and the U.S. timber industry,” (, accessed 4 January 2022.

Saxena, A., Dutta, A., Fischer, H. W., Saxena, A. K., and Jantz, P. (2021). “Forest livelihoods and a “green recovery” from the COVID-19 pandemic: Insights and emerging research priorities from India,” Forest Policy and Economics 131, 1-7. DOI: 10.1016/j.forpol.2021.102550

Sen, M., and Singer, B. (2020). Forests at the Heart of a Green Recovery from the COVID-19 Pandemic (UN/DESA Policy Brief #80), United Nations Department of Economic and Social Affairs Economic Analysis, New York, NY.

Shackletona, C. M., Shackletona, S. E., Buiten, E., and Bird, N. (2007). “The importance of dry woodlands and forests in rural livelihoods and poverty alleviation in South Africa,” Forest Policy and Economics 9(5), 558-577. DOI: 10.1016/j.forpol.2006.03.004

Sivaram, M., and Sandeep, S. (2010). A Decision Support System for Monitoring and Forecasting Timber Prices of Kerala State (KFRI Research Report No: 493), Kerala Forest Research Institute, Kerala, India.

SSI (2020). “Social Security Institution statistics yearbook insured and workplace,” Statistics. ( _istatistik_yilliklari) accessed on 28th April 2022.

Stanturf, J. A., and Mansuy, N. (2021). “COVID-19 and forests in Canada and the United States: Initial assessment and beyond,” Front. For. Glob. Change 4, article no. 666960. DOI: 10.3389/ffgc.2021.666960

Størdal, S., Lien, G., and Trømborg, E. (2021). “Impacts of infectious disease outbreaks on firm performance and risk: The forest industries during the COVID-19 Pandemic,” Journal of Risk and Financial Management 14(7), 1-13. DOI: 10.3390/jrfm14070318

Sujová, A., Michal, J., Kupčák, V., and Dudík, R. (2017). “The impact of international trade of raw wood to the economic growth of forest-based sectors in the Czech and Slovak republics,” BioResources 12(1), 1102-1111. DOI: 10.15376/biores.12.1.1102-1111

Timber Mart-South (2021). “Arkansas timber price report,” (, accessed on 4th January 2022.

Türker, M. F. (2020). Forestry Business Economics, Forestry and Nature Conservation Foundation Publication, Trabzon, Turkey.

UN Turkey (2020). “COVID-19 socioeconomic impact assessment report,” (, accessed on 15th December 2021.

UNECE/FAO (2021). “Forest products annual market review 2020-2021,” (, accessed on 6th January 2022.

Yücel, S., and Durak, İ. (2021). “Investigation of financial impacts of COVID-19 on BIST manufacturing sector firms by financial ratios and statistical techniques,” Journal of Accounting and Finance 2021(90), 101-126. DOI: 10.25095/mufad.813411

Zaremba, A., Kizys, R., Aharon, D. Y., and Demir, E. (2020). “Infected markets: Novel coronavirus, government ınterventions, and stock return volatility around the globe,” Finance Research Letters 35, 1-7. DOI: 10.1016/

Zhang, D., Hu, M., and Ji, Q. (2020). “Financial markets under the global pandemic of COVID-19,” Finance Research Letters 36, 1-6. DOI: 10.1016/

Article submitted: January 11, 2022; Peer review completed: April 25, 2022; Revised version received and accepted: May 9, 2022; Published: May 11, 2022.

DOI: 10.15376/biores.17.3.4030-4042