Abstract
Purpose
The article compares the effect of European Union (EU)-Russian sanctions imposed in 2014 with the influence of fluctuating oil prices on Danish trade.
Design/methodology/approach
In this paper annual import and export trade data between Denmark and 152 countries from the period 2002–18 were computed in STATA/SE 16.1 using the Gravity model to evaluate the effect of economic sanctions and the price of oil.
Findings
Results showed that the impact from the fall of oil price exceeded the negative effect from sanctions on Danish export. Additionally, the analyses suggest that the fall in oil price had a negative effect on Danish import. Even so, Danish import significantly increased due to growth in supplies of energy resources from Russia.
Originality/value
This study explains the overlapping effects of EU-Russian sanctions and fluctuating oil prices on Danish trade. This methodology can be expanded to encompass multiple countries using the two-sided Gravity model.
Keywords
Citation
Larsen, K.S. (2022), "Influence of EU-Russian sanctions and oil price on Danish trade", Journal of International Logistics and Trade, Vol. 20 No. 2, pp. 102-115. https://doi.org/10.1108/JILT-05-2022-0005
Publisher
:Emerald Publishing Limited
Copyright © 2022, Kseniia Skogstad Larsen
License
Published in Journal of International Logistics and Trade. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Denmark, as member of the European Union (EU), had been building long-term relations with Russia until the Ukrainian crisis. Since signing The Partnership and Cooperation Agreement on 1 December 1997, Russia and EU held 32 summits. In 2010, the Partnership for Modernization Program between EU and Russia was initiated (European Commission, 2010), and on 22 August 2012, Russia joined the World Trade Organization (WTO), which was a positive step towards international co-operation (WTO, 2020). However, the strengthening of economic relations between Russia and EU was partially interrupted by the onset of the Ukrainian crisis in 2014.
In March 2014, in response to Russia's military intervention in Eastern Ukraine, the European Council implemented sanctioning measures against Russia. The EU criticised the illegal annexation of Crimea and intervention against Ukraine's sovereignty and independency. On 17 March 2014, EU with a number of other states [1], decided to use political, diplomatic and sectoral economic sanctions against Russia. Relations between EU and Russia deteriorated further when the Malaysia Airlines Flight 17 was shot down while flying over Eastern Ukraine. After this incident, on 22 July 2014, the EU launched the next stage of sectoral and financial sanctions, targeting the largest Russian banks, energy and defence entities (Council of the European Union, 2021). In August 2014, in response to European sanctions, Russia decided to implement a food ban on imports of final food products and food raw materials from the EU and other countries (Putin, 2014).
The food ban covers most agricultural products from EU, USA, Norway, Canada and Australia (Putin, 2014). In 2013, before the sanctions, Russia was the second largest market for EU agricultural exports with a total export value of Euro (EUR) 11.8 bil. accounting for about 10% of EU's export of these goods. The products covered by the import ban made up 43% of EU's agricultural export to Russia (approx. EUR 5 bil.) (Hanne Lauger, 2014). Regarding this, on 5 September 2014, the Danish ministry of Food, Agriculture and Fisheries announced possible market measures proposed by the EU to address the market impact and the concerns about potential trade losses. Under the EU Common Agricultural Policy, the EU Commission suggested the following market measures: limiting market supply in order to stabilize prices of agri-foods; assistance with food storage for producers; export refunds; other measures to resolve specific market problems; etc (European Commission, 2014).
Out of EUR 627 mil. Danish agri-food export to Russia in 2013, the products that were later covered by the food ban amounted to EUR 341 mil. (European Commission, 2014). Denmark's total export of pork to Russia was 700,000 ton. (2012), beef 3,000 ton. (2013), poultry 4,000 ton. (2013), butter 2,450 ton. (2013) and cheese 18,247 ton. (2013) (Hanne Lauger, 2014).
EU imposed a number of economic sanctions targeting exchanges with Russia in specific economic sectors, such as military production, financial sector and energy sector (Council of the European Union, 2021). As a result of these sanctions, Russian companies and banks lost access to long-term European capital, and the Russian energy sector was restricted access to certain sensitive technologies and services for oil production and exploration. On the other hand, the EU has been retaining partial dependence on Russian energy resources. In 2014, the Russian share of EU import of crude oil was 31% of the total volume, gas 33.4% and solid fossil fuels 23.6% (Eurostat, 2020a). In the period 2013–2018, Russia increased its energy supplies to the European market and was poised to strengthen its EU market share after the launch of the Nord Stream-2 pipeline. In 2018, the Russian share of EU import of crude oil decreased to 29.8%, while solid fuel and natural gas increased to 42.3 and 40.1%, respectively. Compared to the year 2000, today Denmark has lost its energy independence, although it still has one of the lowest dependency rates [2] in the EU. In 2000, the Danish dependency rate was -35.9%, and in 2018 the percentage of Danish energy imports had increased to 23.7% (Eurostat, 2020a).
1.1 Danish trade with Russia before and after sanctions
According to Statistics Denmark, the largest export partners for Denmark are Germany, Sweden and Great Britain. Trade with countries outside the EU, e.g. China and USA, also play a significant role. In the period 2012–2018, the German share of total Danish export reached at most 20%, while Sweden had a share of 15%. The maximum volume of Danish export to Russia in 2011 reached almost 2% of the total export, corresponding to Danish Krone (DKK) 11,966 mil. (Statistics Denmark, 2020). After the implementation of sanctions in 2014, the share of direct export to Russia fell to 0.88%. In the same period, Germany also had a decline in its share of total Danish exports, while Sweden's share remained approximately at the same level (12%). From the Russian side, Germany remained the second biggest import partner after China, whereas exports from Germany to Russia fell by 50% between 2013 and 2015 (detailed information in Appendix).
According to Comtrade statistics, since 2014, Danish export to Germany, Sweden, Norway and Finland significantly dropped and began slightly recovering in 2017. It is possible that a part of the Danish export to these countries were re-exported to Russia; this could explain the decrease in export in 2015 as shown by the trade curves in Figure 1. However, this seems improbable as there was no increase in Danish export to Belarus or Kazakhstan in this period. Despite this, insignificant re-export flows from the Eurasian Economic Union (EAEU) member-countries cannot be completely excluded. In 2014, total Danish exports stalled; however, already in 2015, it showed a positive trend due to an increase in trade volumes with small partner states.
The total decline of Danish export to Russia in 2018 relative to 2013 was DKK 5,570 mil. (47%). The drop that is directly related to the implementation of the Russian embargo on food exports is DKK 3,510 mil., which accounts for 63% of the total export decline and corresponds to a 75% drop in the affected categories of live animals, food, beverages and tobacco (Statistics Denmark, 2020). There was also a significant decline in the export of machinery excl. Transport equipment of DKK 1,191 mil. (38.8%) (Statistics Denmark, 2020).
Five years after implementation of bilateral sanctions, only one export category (crude materials, inedible, except fuels) has returned to the pre-sanctioned level. All other categories showed a decline, which can be explained by a general reduction in Russian demand. In the period 2015–16, when the oil prices were low, the Russian ruble lost its value, and imported foreign goods became expensive for Russian consumers. The same mechanism manifests itself in companies that are trying to reduce dependence on expensive imports, and, if possible, to replace it. Yet another possible factor is the limitation on export financing, which is directly linked to EU's financial restrictions. There were several exceptions for export credit agencies in the EU, which could provide financing to targeted entities to support exports of non-prohibited goods from the EU. Despite this, the danger of being fined by supervisory authorities for violating the sanctions reduced the number of transactions.
In general, Russian export to Denmark was not part of the EU's sanctions, and Russian goods were not boycotted by European consumers. As seen in Figure 2, total Danish import from Russia increased by DKK 4,793 mil. (ca 60%) from 2013 to 2018. A significant increase of DKK 3,346 mil. was in the category “mineral fuels, lubricants and related materials”. The growth in this category was driven by increased sales in gas oils and fuel oils by DKK 1,405 mil., iron and steel by DKK 1,065 mil. and petroleum oils by DKK 465 mil. Import growth (DKK 1,095 mil.) of the manufactured goods category was induced by increased demand for light and medium oils (e.g. motor spirits). The remaining growth was in agricultural goods by DKK 347.3 mil (Statistics Denmark, 2020).
Denmark is a self-sufficient gas-producing country as Danish gas production is bigger than consumption. According to the Danish Utility Regulator (Danish Utility Regulator, 2019), the Danish gas consumption has been relatively stable since 2014. Denmark has two gas importers: Norway and Germany. However, Russian gas is supplied to Denmark as a share of the imported gas from Germany. Approximately 75% of imported gas is provided by Norway.
Supply of oil and petroleum products to Denmark is sufficiently diversified. Norway has been taking the leader position, but its share is more modest. The second biggest supplier remains Russia with around a 15% share in 2018 (Eurostat, 2020b). In non-energy categories, supply growth from Russia is most likely associated with the depreciation of the Russian ruble, caused by the fall in oil prices in 2015–16.
1.2 Research questions and hypotheses
The main objective of this article is to examine the impact of EU-Russian sanctions on total Danish trade. Expectedly, apart from sanctions, a critical factor influencing world trade is the oil price. The price of energy commodities remains the most important economic indicator for petrostates, such as Russia, as they are heavily dependent on the revenues from oil and gas production. Low oil prices bring economic harm to energy companies and increase state budget deficit of petrostates. This negatively influences demand for Danish import, which might have strong effects on tradable goods, domestic prices and the volumes of produced and consumed goods. Thus, there are several reasons to believe that fluctuation in prices of energy resources affected Danish trade more than “soft” political decisions such as sanctions. Therefore, the research question of this article is focused on the consequences from two affecting factors – the fluctuation of oil prices in the period 2002–18 and sanctions between EU and Russia.
Sanctions had negative impact on Danish export.
Sanctions had negative impact on Danish import.
Danish export was less impacted by sanctions than by the fall in oil prices.
Danish import was less impacted by sanctions than by the fall in oil prices.
2. Methodology
Numerous studies have investigated the impact of the Russian food embargo on international trade using the Gravity model, first presented in 1962 by Tinbergen. Skvarciany, Jurevičiene and Vidžiunaite analysed how the Russian food embargo has been affecting EU trade with Russia. The authors evaluated the effect of the embargo on each of EU's member states and concluded, that Germany's export difference before and after embargo was the highest in all EU but recovered quite fast. Most of EU's countries did not suffer significant losses after Russia imposed the embargo (Skvarciany et al., 2020). Related to this article, Crozet and Hinz also evaluated the global and county-level impact of sanctions on trade. The authors found that trade restrictions wiped out most of EU's exports of sanctioned goods to Russia, and the overall sanctions regimes also had side effects on non-sanctioned exports (Crozet and Hinz, 2020).
The Gravity model is based on the simple idea that relative economic size attracts trade with each other while greater distances weaken the attractiveness (Pollins, 1989). Due to good performance in representing international trade, the model gained popularity for estimation of factors affecting trade, migration and investment flows between countries (Anderson and Van Wincoop, 2003). To measure the impact of sanctions and political conflicts on the flows of international trade, the model has been extended to include dummy sanction variables and was widely applied in a number of empirical studies (Caruso, 2003; Crozet and Hinz, 2020; Hufbauer et al., 2007; Lamotte, 2012; Oegg and Hufbauer, 2003). According to Oegg and Hufbauer, the sanction coefficients in the model represent the deviations from the non-sanctioned trade-flow and do not include country specifics to avoid incorrect measurement for the sanctions impact. On this basis, the Gravity model was chosen for the current article to investigate the changes in Danish trade after the imposing of EU-Russian sanctions in 2014.
A basic understanding of the Gravity equation of international trade (1) is that trade flow from country i to country j, denoted by Tij, is proportional to the product of the two countries' gross domestic products (GDPs), denoted by Yi and Yj, and proportional to their distance, Dij.
In order to increase the explanatory power of the model, additional variables could be added to (1), giving the following equation:
2.1 Model specification
The model specifications (3) and (4) are based on equation (2). However, as this research only applies to trade-flows with Denmark, the one-sided version of the Gravity model is suitable. This means that dependent and independent variables only vary by j – recipient countries in the case of export and source country in the case of import. Usually, the parameters in the Gravity model are obtained by the logarithmic transformation.
The one-sided version of (2) converted into log-linear form to estimate the model parameters using the Ordinary Least Square (OLS) method, as introduced by Anderson and Wincoop (Anderson and Van Wincoop, 2003) is written as
Silva and Tenreyro point out the presence of heteroskedasticity in log-linearization of the empirical model that leads to inconsistent estimates (Santos Silva and Tenreyro, 2006). Because of incompatibility with zero trade flows, the authors recommend applying a Poisson pseudo-maximum likelihood (PPML) estimator as an alternative for the standard log-linear model. Furthermore, the PPML with FE technique is a natural way to deal with zero-valued trade flows and avoids the under-prediction by generating estimates without logarithms of trade flows. The stochastic equation of PPML (4) can be written as
To minimise the risk of inconsistent estimates, zero and negative flows are usually excluded from the data sample, even when using the PPML technique. Martin and Pham (2020) indicated unsuitability of PPML in situations with a large number of zero flows. Therefore, to directly compare results from PPML with OLS techniques, the same sample will be used. In addition to the PPML model with country- and year-FE, a PPML model without FE will be applied to keep explanatory variables from being omitted.
Each method has advantages and disadvantages and none of them can completely exclude bias in the estimation. As none of the methods is clearly superior, using several estimation methods in this study gives the opportunity to control for unobserved heterogeneity and obtain unbiased results.
2.2 Data and variables
In line with the objectives of the study, dependent variables are annual Danish trade flows from countries of origins (importers) and to destination countries (exporters) in the period 2002–18. Danish trade, in this study, excluded trade flows from Greenland and the Faroe Islands, which are the part of the Kingdom of Denmark. This is due to the fact that Greenland and the Faroe Islands are two autonomous territories, and the Faroese government refused to support EU sanctions on Russia in 2014 (Martin Breum, 2018).
Danish trade flows were retrieved from the UN Comtrade database (UN Comtrade, 2020). Trade flows indicate the value of trade goods without services and technologies. The gravity variables GDP and GDP per capita were assembled using The World Bank Open data (The World Bank, 2020). Annual average The Organisation of the Petroleum Exporting Countries (OPEC) oil prices in the period 2002–18 were retrieved from Statista (2020). REER measures the real value of a country's currency against the basket of the trading partners. This annual indicator is consumer price index (CPI)-based and has been calculated for all trade partners in the period 2002–18 and was extracted from Bruegel dataset (Bruegel Datasets, 2020). This variable could help estimate possible impact of depreciation of the Russian ruble on Danish trade with Russia. The geographical distances were calculated using coordinates of capital cities from The Centre d'Études Prospectives et d'Informations Internationales (CEPII) research centre (Mayer and Zignago, 2011).
The dataset contains annual data for 152 countries in the period 2002–18 of all explanatory variables described above and two dependent variables – Total Danish Export and Total Danish Import. In order to reduce the risk of bias, countries with zero trade flows and countries with missing data were excluded from the dataset. The dataset has no presence of multicollinearity which could influence the estimates. The mean variance inflation factor (VIF) is 1.66 and individual values do not exceed the acceptable level of 10. Breusch-Pagan test showed a significance <0.001 and thus rejects the null hypothesis of homoscedasticity. In order to avoid bias in the analyses, the options of robust standard errors and logarithmic transformation of variables were used. Table 1 shows the list of model variables.
3. Results
Table 2 provides the results of estimation of Total Danish Export in the period 2002–18 using three models. In the models with FE, dummy variables with perfect correlations are omitted. The coefficients for the sanction variable are negative and statistically significant (p < 0.05) for all models. This indicates that EU-Russian sanctions imposed in 2014 have a negative effect on Total Danish Export, supporting Hypothesis 1a. Positive and statistically significant coefficients for Oil price variable mean that higher oil prices are associated with increased Total Danish Export.
The coefficients for sanctions and price of oil cannot be directly compared when evaluating the effect of these two factors on Total Danish Export. Whereas the sanctions variable is a dummy variable and therefore a non-logged regressor, the oil price variable is a logged regressor.
The formula to compute the effect of non-logged regressors is (ebi – 1) × 100%, where bi is the estimated coefficient (Santos Silva and Tenreyro, 2006). Thus, the sanctions impact on Total Danish Export to Russia in OLS model is (e0.5428–1) × 100% = 71.60%. The negative coefficient means that the presence of EU-Russian sanctions reduced Total Danish Export to Russia by 71.60%. However, the greatest possible direct effect of EU-Russian sanctions represents the Russian share on Total Danish Export, which peaked at close to 2% in 2011 (see Appendix). Not accounting for potential increases in export after this year, the maximal estimated negative impact on Total Danish Export caused by EU-Russia sanctions is 1.43%.
The coefficients on logged regressors are elasticities, and there is no need to transform those. Holding all other independent variables constant, each one percent increase in Oil price increases Total Danish Export by 0.1821%. Table 3 contains the modelled impact of fall in oil prices compared to the year 2013.
The overall effect of the fall in oil prices during sanction-years exceeded the greatest possible impact of EU-Russian sanctions (1.43%) on Total Danish Export – Hypothesis 2a is supported. In PPML(FE) and PPML, coefficients for the Oil price variable are higher, which leads to higher impact on Total Danish Export than in the OLS model. Inversely, the sanctions variable has lower coefficients, which means less impact on Danish Export to Russia compared to the OLS model.
Table 4 contains estimates for Total Danish Import in the period 2002–18. Surprisingly, coefficients for the sanction variable are all positive but not statistically significant (p > 0.05) for PPML model, and statistically significant (p < 0.01) for OLS (FE) and PPML (FE) models. Therefore, Hypothesis 1b is rejected. A possible explanation for the positive influence of sanctions is that the growth of imports from Russia is associated with sale of energy resources (see Section 1.1). Positive and statistically significant coefficients for Oil price variable mean that higher oil prices are associated with increased Total Danish Import and inversely. Holding all other variables constant, one per cent increase in Oil price increases Total Danish Import by 0.2806% in OLS (FE) model in Table 5. For other models, results are similar.
In terms of political and economic objectives, sanctions could only negatively affect trade between sender and target countries. Therefore, statistically significant and positive effect from sanctions on Total Danish Import from Russia cannot be compared with modelled impact of the fall in oil price on Total Danish Import. Hypothesis 2b is neither accepted nor rejected.
4. Discussion and conclusion
The analyses resulted in several findings related to the impact of sanction on Danish trade
First, results of the Gravity model indicate that sanctions have direct negative impact on Total Danish Export. The growth in Danish export (10% from 2013 to 2018, see Table A1 in Appendix) indicates that the impact of the sanctions on Total Danish Export was minimal.
Neither the European sanctions nor the Russian sanctions were officially aimed at trade between countries. European smart sanctions are supposedly “targeted” to avoid widespread harm to the Russian economy. According to the Kremlin's official position, the Russian food ban was applied “in order to protect the national interests of the Russian Federation” (Russian Government, 2014), although the very type of direct prohibition on the import of certain categories of goods definitely influences trade with Russia.
Second, the results of the analyses show that the effect from the fluctuation of oil prices influenced Total Danish Export more than the presence of EU-Russian sanctions. The increase in oil price has a positive impact on Total Danish Export as high oil prices have a positive effect on strengthening the Russian national currency.
Third, the results indicate that the growth in oil prices and the presence of sanctions between EU and Russia unexpectedly had a positive and statistically significant impact on Danish Import. Total Danish Import increased by DKK 95,192 mil. from 2013 to 2018, and Russian export to Denmark significantly increased by 1.6 times (a share of almost 1.8% of Total Danish Import). Positive and statistically significant coefficients of sanctions regressors in models related to Total Danish Import may link with depreciation of the Russian ruble. In fact, the decline in the value of the Russian ruble is directly correlated with the oil price. Since 2015, the low oil price made Russian products cheaper for Danish consumers. However, the main growth in demand for Russian import in Denmark is driven by increasing demand for natural resources.
Additionally, Danish Export flows are highly affected by GDP of partner countries which has a positive impact on Danish trade. This could be explained by the fact that strong economies have major international ties with other strong economies. From the PPML model without FE, factors that have a positive influence on Danish trade are: Scandinavian language of partner country, Common state border with Denmark, Membership in EU trade blocs. The geographical distance and landlocked status are two factors associated with higher transport costs and have a negative impact on Danish trade.
Losses from sanctions were not expected to be substantial for Denmark. In terms of volume, Russia was an ordinary trading partner for Denmark. Potential losses have been associated with export of Danish agricultural goods, where a stagnant year in 2014 due to a decrease in supplies to Russia can be observed (more in Table A2 in Appendix). This pause in growth of Total agricultural export is highly likely connected with the Russian food ban. A slight recovery in growth was already evident in 2016, which indicates that Danish producers had adapted to the new conditions. In this context, adaptation could mean indirect sales to Russia via neighbouring within the EAEU, such as Kazakhstan and Belarus. However, the problem of re-export of European goods to Russia requires a deeper empirical analysis. Losses after the imposing of sanctions were minimized already in 2015 as the observed decline in agricultural export in 2014 quickly returned to previous growth. On the other hand, Russia is a huge potentially attractive market to European countries. Some countries had close commercial ties with Russia due to their geographical location or historical past, such as Finland and Poland as well as the Baltic countries which were part of the Soviet Union. For such countries, the sanctions could have had a greater economic impact, brought losses in the production sectors and/or increase in unemployment.
Figures
Description of variables
| Variables | Description | Expected |
|---|---|---|
| Dependent variables | ||
| Danish total export | Log (monetary value of Danish export in mil. USD) 152 countries in the period 2002–18 | |
| Danish total import | Log (monetary value of Danish import in mil. USD) 152 countries in the period 2002–18 | |
| Independent variables | ||
| GDPj | Log (GDP of country j in constant prices 2010 in mil. USD) | +/– |
| GDPj per capita | Log (GDP per capita of country j in constant prices 2010 in USD) | +/– |
| Distancej | Log (Distance between Copenhagen and capitals of country j) | – |
| REERj | Log (Real effective exchange rate of country j, CPI-based) | + |
| Oil price | Log (Annual average OPEC oil price in USD per barrel) | + |
| Dummy variables | ||
| Common language | Trade partners with official Scandinavian languages | + |
| State border | Land border with Denmark | + |
| Landlocked state | All states without access to the sea | – |
| Trade bloc | Membership in EEA or EFTA | + |
| Sanctions | Only for Russia since 2014 | – |
Dependent variable: Total Danish Export in the period 2002–2018
| OLS(FE) Log(Export) | PPML(FE) export | PPML export | |
|---|---|---|---|
| Log(GDP) | 0.5572*** (0.202) | 0.4688 (0.285) | 0.6920*** (0.016) |
| Log(GDP per capita) | 0.4497* (0.264) | 0.4448 (0.302) | 0.2666*** (0.026) |
| Log(Distance) | – | – | −0.4769*** (0.027) |
| Log(Reer) | 0.2860** (0.136) | 0.3487** (0.150) | −0.0111 (0.161) |
| Log(Oil price) | 0.1821*** (0.035) | 0.2906*** (0.030) | 0.2894*** (0.036) |
| Dummy ScandLand | – | – | 1.0543*** (0.050) |
| Dummy StateBorder | – | – | 0.4614*** (0.049) |
| Dummy LandLocked | – | – | −0.6882*** (0.045) |
| Dummy TradeBlocs | – | – | 0.4422*** (0.058) |
| Dummy Sanctions | −0.5428*** (0.027) | −0.5092*** (0.017) | −0.3697*** (0.102) |
| Cons | −16.0584*** (3.378) | – | −12.4282*** (0.741) |
| N | 2,518 | 2,518 | 2,518 |
| adj. R-sq | 0.82 | – | 0.947 |
Note(s): Robust standard errors in parentheses
*p < 0.1, **p < 0.05, ***p < 0.01
Modelled impact of the fall in oil price on Total Danish Export
| Time periods | 2013–14 | 2013–15 | 2013–16 | 2013–17 | 2013–18 |
|---|---|---|---|---|---|
| Decrease in oil price in % | 9 | 53 | 61 | 50 | 34 |
| Negative impact on total Danish export in % | 1.63 | 9.65 | 11.1 | 9.1 | 6.2 |
Dependent variable: total Danish import in the period 2002–2018
| OLS(FE) Log(Import) | PPML(FE) import | PPML import | |
|---|---|---|---|
| Log(GDP) | 0.5485 (0.859) | 0.1500 (0.448) | 0.8138*** (0.030) |
| Log(GDP per capita) | 0.6232 (1.057) | 0.6724 (0.515) | −0.1451*** (0.047) |
| Log(Distance) | – | – | −0.6699*** (0.042) |
| Log(Reer) | −0.1370 (0.458) | 0.1880 (0.197) | 0.8258*** (0.210) |
| Log(Oil price) | 0.2806*** (0.069) | 0.2932*** (0.023) | 0.2825*** (0.044) |
| Dummy ScandLand | – | – | 1.1513*** (0.085) |
| Dummy StateBorder | – | – | 0.3897*** (0.069) |
| Dummy LandLocked | – | – | −0.3955*** (0.069) |
| Dummy TradeBlocs | – | – | 0.8003*** (0.079) |
| Dummy Sanctions | 0.2966*** (0.063) | 0.3322*** (0.019) | 0.0424 (0.125) |
| Cons | −17.1822 (12.679) | – | −14.2823*** (1.234) |
| N | 2,518 | 2,518 | 2,518 |
| adj. R-sq | 0.722 | – | 0.919 |
Note(s): Robust standard errors in parentheses
*p < 0.1, **p < 0.05, ***p < 0.01
Modelled impact of the fall in Oil price on Total Danish Import
| Time periods | 2013–14 | 2013–15 | 2013–16 | 2013–17 | 2013–18 |
|---|---|---|---|---|---|
| Decrease in Oil price in % | 9 | 53 | 61 | 50 | 34 |
| Negative impact on total Danish import in % | 2.52 | 14.84 | 17.08 | 14 | 9.52 |
Danish trade between 2012 and 2018
| Total Danish trade between 2002 and 2018 in mil. DKK | |||||||
|---|---|---|---|---|---|---|---|
| Year | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 |
| Total Danish Import in mil. DKK | |||||||
| Total Danish import | 528,678.05 | 545,969.83 | 555,243.21 | 573,057.55 | 568,247.74 | 607,348.94 | 641,161.85 |
| From Russia | 4266.59 | 6955.91 | 6686.07 | 9210.02 | 9580.96 | 10933.03 | 11362.71 |
| From Germany | 110,352.50 | 114,612.90 | 114,109.40 | 119,603.60 | 123,031.80 | 129,602.60 | 144,957.30 |
| From Sweden | 68233.14 | 67411.52 | 68265.52 | 69491.12 | 68652.16 | 72025.22 | 75682.42 |
| Total Danish agricultural import | 70,576.60 | 73,749.90 | 75,480.70 | 78,670.40 | 78,662.40 | 81,915.80 | 84,946.80 |
| Total Danish export in mil. DKK | |||||||
| Total Danish export | 614,546.90 | 620,270.40 | 620,622.80 | 636,133.80 | 637,315.40 | 669,193.00 | 685,153.70 |
| To Russia | 11,498.60 | 11,873.30 | 8,712.60 | 5,629.20 | 5,539.90 | 6,276.40 | 6,303.10 |
| To Germany | 92,027.00 | 100,244.70 | 110,028.80 | 111,694.30 | 100,801.00 | 102,096.10 | 107,147.10 |
| To Sweden | 81,407.70 | 76,784.90 | 74,016.50 | 73,586.20 | 74,919.40 | 78,425.90 | 78,620.60 |
| Total Danish agricultural export | 111,441.40 | 114,740.50 | 114,051.80 | 115,956.70 | 119,198.30 | 126,335.60 | 122,480.00 |
| Share of total Danish import in % | |||||||
| From Russia | 0.81 | 1.27 | 1.2 | 1.61 | 1.69 | 1.8 | 1.77 |
| From Germany | 20.87 | 20.99 | 20.55 | 20.87 | 21.65 | 21.34 | 22.61 |
| From Sweden | 12.91 | 12.35 | 12.29 | 12.13 | 12.08 | 11.86 | 11.8 |
| Share of total Danish export in % | |||||||
| To Russia | 1.87 | 1.91 | 1.4 | 0.88 | 0.87 | 0.94 | 0.92 |
| To Germany | 14.97 | 16.16 | 17.73 | 17.56 | 15.82 | 15.26 | 15.64 |
| To Sweden | 13.25 | 12.38 | 11.93 | 11.57 | 11.76 | 11.72 | 11.47 |
Source(s): www.statbank.dk
Total export from Finland, Germany and Sweden to Russia
| Total Finish, German and Swedish export to Russia in mil. USD | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | |
| Finland | 6158.81 | 7321.42 | 7217.94 | 7022.69 | 6069.24 | 3443.65 | 3234.45 | 3795.55 | 3852.14 |
| Germany | 35937.58 | 49359.62 | 50180.98 | 48738.49 | 39845.21 | 24649.52 | 24515.88 | 29850.72 | 30426.87 |
| Sweden | 2789.74 | 4095.74 | 3365.40 | 3531.22 | 3144.67 | 1701.90 | 1656.42 | 2135.23 | 2192.39 |
Source(s): UN Comtrade database comtrade.un.org
Notes
USA, Canada, Australia, New Zealand, Switzerland, Norway, Ireland, Montenegro, Albania, Liechtenstein, Japan etc.
The energy dependency rate shows the proportion of energy that an economy must import. It is defined as a net energy import: imports minus exports.
References
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