Characteristics of the Supply Chain of Tobacco and Tobacco Products: Evidence from Serbia
Abstract
:1. Introduction
- Through excise taxes, the state affects the price of cigarettes, thus collecting revenues and potentially reducing consumption, which implies a reduction in the demand for raw tobacco.
- It determines the game’s rules in this market through the appropriate legal regulation.
- In some cases, its agricultural policy measures affect tobacco production by providing various support to tobacco producers.
- This research examined the entire supply chain of tobacco, and thus fills the gap in the literature, especially in the European territory.
- Based on the results, all participants in the supply chain can adjust their operations so that the supply chain remains sustainable.
- Based on the research, it is possible to determine the critical problems within the chain and give adequate recommendations to the creators of economic policies.
2. Literature Review
3. Materials and Methods
4. Results
5. Discussion
- The producers are in a poor negotiating position due to market concentration conditioned by the relatively low price of tobacco (Figure A3). Also, according to the Law on Tobacco [6], agricultural farms are obliged to enter a contract with tobacco processors and to sell tobacco to processors by the end of the current year. This kind of law puts farmers in a worse position than processors because the free sale of tobacco on the market is impossible.
- As already mentioned, farms perform the process of drying and packaging tobacco, which requires additional capital investments to purchase dryers. The energy consumption for drying is relatively high (natural gas is used most often), which increases production costs, especially in cases of shocks in the energy market, which was a characteristic of the observed period.
- Tobacco production requires a relatively large number of seasonal workers, which is a limiting factor. With the economic development in Serbia, there has been a significant labor force migration toward industry, while specific technological solutions are still expensive for producers. Indeed, reducing the number of farms is a characteristic of Serbian agriculture in the transition period, which also affected the tobacco production sector.
6. Conclusions
- Serbia was the only country in Europe where tobacco production was increasing. The key reasons were the presence of the largest multinational companies and weaker state regulations than in the EU.
- The number of farms producing tobacco decreased in the previous period, which, along with the production growth, suggests that the most efficient farms survived on the market. The further survival of these farms was threatened mainly due to a worse negotiating position on the market, which affected the relatively low price of tobacco and the increase in production costs due to the unstable global energy market. One of the solutions is a change in state regulations that will allow farms to sell tobacco freely on the market and encourage the association of producers.
- There was a high market concentration in the Serbian tobacco industry. In the long term, this can potentially impact welfare losses primarily due to the manipulative abilities of oligopoly or oligopsony participants.
- The consumption of cigarettes was very high in Serbia. As tobacco products harm health, government policy must focus on measures that will reduce consumption. An adequate tax policy could affect this reduction and provide additional fiscal revenues.
- Regarding foreign trade, there was a significant intensification, tobacco products were mainly exported to non-traditional markets (Algeria), and exports were dominated by one company—PMI. The tobacco and tobacco products market in Serbia was generally well integrated with the world market, but the level of revealed comparative advantages was low.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Variable | Notation | Formulation | Indicator | Predicted Effect |
---|---|---|---|---|
Profitability | ROA | Net income/Total assets | Company’s capacity to generate profits derived from its assets. | / |
Market concentration (operating revenue-based) | HHI | Equation (1) | Extent to which a market is dominated by a small number of large companies. | + |
Liquidity | LIQ | Current assets/Current liabilities | Company’s capacity to fulfill its short-term financial obligations. | − |
Financial leverage | LEV | Total liabilities/Equity | Company’s indebtedness in relation to equity. | − |
Debt ratio | DEBT | Total liabilities/Total assets | Company’s indebtedness in relation to total assets. | − |
Firm size | SIZE | Ln (Total assets) | Size of organization through total assets. | + |
Tangibility | TANG | Fixed assets/Total assets | Company’s asset structure. | − |
Total assets turnover | TAT | Sales revenue/Average total assets | Company’s capacity to generate sales derived from its assets. | + |
Fixed assets turnover | FAT | Sales revenue/Average fixed assets | Company’s capacity to generate sales derived from its fixed assets. | + |
Current assets turnover | CAT | Sales revenue/Average current assets | Company’s capacity to generate sales derived from its current assets. | + |
Growth | GRW | Turnover (year t) − Turnover (year t1)/Turnover (year t − 1) | Company’s ability to increase sales between two time periods. | + |
Profitability | ROA | Net income/Total assets | Company’s capacity to generate profits derived from its assets. | / |
Market concentration (operating revenue-based) | HHI | Equation (1) | Extent to which a market is dominated by a small number of large companies. | + |
Liquidity | LIQ | Current assets/Current liabilities | Company’s capacity to fulfill its short-term financial obligations. | − |
Financial leverage | LEV | Total liabilities/Equity | Company’s indebtedness in relation to equity. | − |
Debt ratio | DEBT | Total liabilities/Total assets | Company’s indebtedness in relation to total assets. | − |
Firm size | SIZE | Ln (Total assets) | Size of organization through total assets. | + |
Tangibility | TANG | Fixed assets/Total assets | Company’s asset structure. | − |
Total assets turnover | TAT | Sales revenue/Average total assets | Company’s capacity to generate sales derived from its assets. | + |
Fixed assets turnover | FAT | Sales revenue/Average fixed assets | Company’s capacity to generate sales derived from its fixed assets. | + |
Current assets turnover | CAT | Sales revenue/Average current assets | Company’s capacity to generate sales derived from its current assets. | + |
Growth | GRW | Turnover (year t) − Turnover (year t − 1)/Turnover (year t − 1) | Company’s ability to increase sales between two time periods. | + |
Year | Area (ha) | Total Production (t) | Yield (t/ha) | Number of Farms | Production per Farm (t) | Area per Farm |
---|---|---|---|---|---|---|
2013 | 4939 | 7977 | 1.62 | 1781 | 4.48 | 2.77 |
2014 | 4899 | 9341 | 1.91 | 1695 | 5.51 | 2.89 |
2015 | 5012 | 8776 | 1.75 | 1235 | 7.11 | 4.06 |
2016 | 5256 | 7810 | 1.49 | 959 | 8.14 | 5.48 |
2017 | 5069 | 7173 | 1.42 | 983 | 7.30 | 5.16 |
2018 | 5762 | 7169 | 1.24 | 992 | 7.23 | 5.81 |
2019 | 7023 | 7992 | 1.14 | 885 | 9.03 | 7.94 |
2020 | 6745 | 8924 | 1.32 | 900 | 9.92 | 7.49 |
2021 | 5803 | 10,097 | 1.74 | 775 | 13.03 | 7.49 |
Herfindahl–Hirschman Index | Operating Revenue | Net Income | Equity | Number of Employees |
---|---|---|---|---|
HHI 2013 | 0.484 | 0.839 | 0.455 | 0.496 |
HHI 2014 | 0.451 | 0.953 | 0.523 | 0.193 |
HHI 2015 | 0.476 | 0.702 | 0.599 | 0.238 |
HHI 2016 | 0.479 | 0.949 | 0.656 | 0.272 |
HHI 2017 | 0.307 | 0.583 | 0.587 | 0.254 |
HHI 2018 | 0.314 | 0.463 | 0.525 | 0.252 |
HHI 2019 | 0.335 | 0.453 | 0.344 | 0.242 |
HHI 2020 | 0.323 | 0.355 | 0.328 | 0.251 |
HHI 2021 | 0.324 | 0.337 | 0.312 | 0.238 |
Test | p-Value | Decision |
---|---|---|
Hausman test | 0.9870 | The random effects model was appropriate |
Time effect | 0.0000 | Time effect included |
Individual effect | 0.0000 | Individual effect included |
Variable | VIF | 1/VIF (TOL) |
---|---|---|
HHI | 1.19 | 0.8382 |
LIQ | 1.23 | 0.8152 |
LEV | 1.17 | 0.8556 |
DEBT | 1.30 | 0.7695 |
SIZE | 1.82 | 0.5493 |
TANG | 3.78 | 0.2645 |
TAT | 10.82 | 0.0925 |
FAT | 7.25 | 0.1379 |
CAT | 4.67 | 0.2142 |
GRW | 1.23 | 0.8128 |
Mean VIF | 3.45 | - |
Test | p-Value | Decision |
---|---|---|
Wooldridge test | 0.2556 | Absence of autocorrelation |
Breusch–Pagan test/Cook–Weisberg test | 0.0022 | Presence of heteroskedasticity |
ROA | Coefficient | Robust Standard Error | z | P > |z| | 95% Conf. | Interval |
---|---|---|---|---|---|---|
HHI | −0.5684 | 0.1872 | −3.04 | 0.002 | −0.9352 | −0.2016 |
LIQ | −0.0008 | 0.0003 | −2.84 | 0.005 | −0.0014 | −0.0002 |
LEV | 0.0047 | 0.0025 | 1.91 | 0.057 | −0.0001 | 0.0096 |
DEBT | −0.0712 | 0.0010 | −7.13 | 0.000 | −0.0907 | −0.0516 |
SIZE | −0.0124 | 0.0077 | −1.61 | 0.107 | −0.0275 | 0.0027 |
TANG | −0.1868 | 0.0928 | −2.01 | 0.044 | −0.3686 | −0.0049 |
TAT | 0.1552 | 0.0633 | 2.45 | 0.014 | 0.0311 | 0.2792 |
FAT | −0.0235 | 0.0093 | −2.54 | 0.011 | −0.0417 | −0.0053 |
CAT | 0.0128 | 0.0205 | 0.62 | 0.533 | −0.0273 | 0.0529 |
GRW | −0.0446 | 0.0111 | −4.00 | 0.000 | −0.0664 | −0.0228 |
Constant | 0.6091 | 0.2237 | 2.72 | 0.006 | 0.1706 | 1.0477 |
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Tica, T.; Matkovski, B.; Đokić, D.; Jurjević, Ž. Characteristics of the Supply Chain of Tobacco and Tobacco Products: Evidence from Serbia. Agriculture 2023, 13, 1711. https://doi.org/10.3390/agriculture13091711
Tica T, Matkovski B, Đokić D, Jurjević Ž. Characteristics of the Supply Chain of Tobacco and Tobacco Products: Evidence from Serbia. Agriculture. 2023; 13(9):1711. https://doi.org/10.3390/agriculture13091711
Chicago/Turabian StyleTica, Teodora, Bojan Matkovski, Danilo Đokić, and Žana Jurjević. 2023. "Characteristics of the Supply Chain of Tobacco and Tobacco Products: Evidence from Serbia" Agriculture 13, no. 9: 1711. https://doi.org/10.3390/agriculture13091711