Tourism in a Remote Nordic Region: Vat, Internet, Oil, English, Distance, Hofstede, and Christianity

Abstract

What are the determinants of tourism when treated as exports in national accounts? Is tourism sensitive to value-added taxation, Internet access, oil, English, Christianity, and regional trade agreements? Impact of these factors on tourism are tested, as well as the potential effects of Hofstede’s cultural dimensions; these are Hofstede’s cultural dimensions of uncertainty, individualism, power distance, masculinity, and orientation. The relationship between variables in the time period of 2003–2016 is analysed in the current research. The research shows estimate for tourism in logarithms to capture the marginal effects of various factors on tourism. The current research also obtains and tests international values for these factors empirically. The research seeks to answer if these factors affect the willingness of foreign tourists to visit.

Keywords:

• Value added tax VAT
• Tourism
• Internet
• Oil
• Hofstede
• Regional Trade Agreements; English and Christianity

Subjects:

• F10
• F12
• H2

PUBLIC INTEREST STATEMENT

This research focuses on the determinants of tourism in a remote Nordic region. The question is how tourism is affected by value-added tax in tourism, the Internet availability, supply of oil with subsequent rise in oil prices impacting air flights, how common the use of English is within the country, distance between the departure and arrival places, and cultural difference between countries of departure and arrival, and finally, the research accounts for how much of the population have Christian believers and if it affects tourism flow. The relationship between all of these factors is analyzed over the time period of 2003 through 2016 in the current research. The research seeks to answer if these factors affect or the differences in these factors impact the willingness of foreign tourists to visit.

1. Introduction

Northern Europe has become a popular tourist destination (Helgadottir, Einarsdottir, Burns, Gunnarsdottir and Matthiasdottir, 2019), with growth achieving new records (OECD, 2019). The focus of this article is on Iceland as a case of remote economies; there, tourism is classified as exports by national accounts. Tourism is estimated by factors like value-added tax (VAT), an indirect tax applied in Europe (WTO Business Council, 1998) that is visible to tourists through listed prices, which has reached up to 25%. Other variable effects are also captured, like the impact of GDP and distance, known in the gravity model (Bergstrand, 1985). Also, impacts of the price of oil and Internet access were estimated. Other variables include Hofstede’s cultural dimensions, common language (Rose, 2004; Wesselbaum & Aburn, 2019), and religion (Crouch, 2007) as they often reflect historical or cultural reasons which may stimulate trade between countries.

Income from foreign tourists has been important in northern countries that typically offer summer vacationing opportunities. However, tourism industry has only recently been developing in some of the small Northern European economies (World Bank, 2019). One of them is Iceland, an isolated island in the North Atlantic Ocean, where tourism has become the single most important export industry. Iceland is the country that serves as the focus of this research.

Governments use taxes to govern consumer behavior, and VAT as a tax on tourism is a macro-economic tool for managing tourism that provides governments with revenue largely paid by foreigners rather than by local taxpayers.

This research first tested the effects of VAT, the GDP wealth effects of the home and host countries, and the impact of higher oil prices and better Internet access on tourism. Then, the research continued by also testing how distance affects tourism inflow. Moreover, this research tested how regional trade agreements (RTAs), English as a primary language, religion, and law impact tourism. Finally, the impact on tourism by the multiple dimensions of Hofstede’s cultural dimensions was tested by investigating the effects of power distance, individualism, masculinity, uncertainty avoidance, and long-term orientation.

2. Variable definition

The variable Tourists accounts for foreign visiting tourists (Gil-Pareja, Llorca-Vivero, & Martínez-Serrano, 2007;Kristjánsdóttir, 2016b; Lim, 1997 Ocampo, Aguilar, & Dagostino, 2019; Witt & Witt, 1995). Tourists as a dependent variable replaces the conventional dependent variable trade in the gravity model (Kristjánsdóttir, 2019). This is because incoming tourists generate foreign currency, classified as exports in national accounts.

The VAT variable is for value-added taxes. Previous studies have estimated the effects of increasing taxes (Kristjánsdóttir, 2017), investigated how VAT influences tourism (Jensen & Wanhill, 2002; Kristjánsdóttir, 2016a), and examined tourism classified as a trade in a small open economy (Kristjánsdóttir, 2013; Massidda & Etzo, 2012).

GDP_home is a variable for the GDP of the departing country, and GDP_host is the GDP of the arrival country. GDP explains trade while allowing for the scale of economies (Krugman, 1991). It explains exports in the basic gravity equation by Bergstrand (1985).

The Oil variable is the Europe Brent Spot Price FOB (in dollars per barrel). Brent crude is a major trading classification of petroleum (FOB stands for freight on board).

The Internet variable definition records the number of Internet users in terms of those with access to the World Wide Web (WWW).

Distance is a variable that accounts for the distance between the tourist’s home country and the host country (Bergstrand, 1985; Davies & Kristjánsdóttir, 2010).

The RTA variable indicates a regional trade agreement if it has significant effects on tourists as they encounter trade blocs when travelling (Gil-Pareja, Llorca-Vivero, & Martínez-Serrano, 2007; Kristjánsdóttir, 2012, 2013).

English is a language variable used to measure if language affects tourists travelling (Leslie & Russell, 2006).

The Christianity variable measures beliefs of nations with respect to the Christian religion influencing tourists travelling since some are sensitive to religious beliefs in the countries to which they travel.

Law is a variable measuring legal changes. The inclusion of this variable accounting for changes in the legal environment is valuable because it indicates if a country is more easily accessible or not (Kristjánsdóttir, Guðlaugsson, Guðmundsdóttir, & Aðalsteinsson, 2017). The Hofstede culture measure has been applied in association with trade (Davies, Ionascu, & Kristjánsdóttir, 2008; Kristjánsdóttir et al., 2017, 2019). Hofstede (1991, 2001) provides Index scores and ranks for countries and regions.

Pow-Dis is a variable for the first cultural measure, power distance. A high value indicates more acceptance of a less-equal society (Hofstede, 1991, 2001).

Ind is a variable for the second cultural measure, individualism. A high value indicates more individualistic societies (Hofstede, 1991, 2001).

Mas is a variable for the third cultural measure, masculinity. A high value of masculinity indicates societies favoring more competition (Hofstede, 1991, 2001).

Uncer is a variable for the fourth cultural measure, uncertainty. A high rank indicates uncertainty-avoiding cultures with people preferring structured situations reflected in traditions (Hofstede, 1991, 2001).

Ori is a variable for the fifth cultural measure, orientation. A high value indicates more long-term orientation in societies with an emphasis on persistence (Hofstede, 1991, 2001).

The variables were then set up as a system of equations in a gravity model specification setting as follows:

(1) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_{4}Oi{l}_{j,t}+{\beta }_{5}Interne{t}_{i,t}+{\text{Ψ}}_{ij,t}.$(1)

The addition of the Distance variable yields the following:

(2) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_4\ln \left(Distanc{e}_{ij}\right)+{\beta }_{5}Oi{l}_{j,t}+{\beta }_{6}Interne{t}_{i,t}+{\varsigma }_{ij,t}.$(2)

Then, I expand the ample and test it including the variables RTA, English, Christianity, and Law:

(3) $ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}RT{A}_{i,t}+{\omega }_{3}Englis{h}_{i,t}+{\omega }_{4}Christianit{y}_{i,t}+{\omega }_{5}La{w}_{i,t}+{\xi }_{i,t}.$(3)

Finally, I test the model with Hofstede’s cultural dimensions of power distance (Pow_Dis), individualism (Ind), masculinity (Mas), uncertainty (Uncer), and orientation (Ori):

(4) $\begin{array}{rl}& ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}Distanc{e}_{ij}+{\omega }_{3}RT{A}_{i,t}+{\omega }_{4}Englis{h}_{i,t}+{\omega }_{5}Christianit{y}_{i,t}\\ & +{\omega }_{6}La{w}_{i,t}+{\omega }_{7}Pow\mathrm{\_}Di{s}_j+{\omega }_{8}In{d}_j+{\omega }_{9}Ma{s}_j+{\omega }_{10}Unce{r}_j+{\omega }_{11}Or{i}_j+{\xi }_{i,t}\end{array}$(4)

The Tourists variable accounted for tourists visiting Iceland in the 14 years of 2003–2016, obtaining the values from the Icelandic Tourist Board (2019).

The VAT variable for value-added tax can change over time t and varies among countries j. More specifically, the VAT variable accounts for the VAT rate on accommodation services. The hospitality industry applies VAT when customers pay their bills in hotels, restaurants, cafes, and bars. If VAT changeswithin a year, which can happen with tax changes, using the latest VAT value. It is from HOTREC, an association of hotels, restaurants, cafes, and bars in Europe (HOTREC, 2019).

GDP_home is the GDP data of the home or departing country from the World Bank (2019).

GDP_host is the GDP data of the host or arrival country obtained from the World Bank (2019).

Oil price accounts for the world oil price; the value varies over the years 2003 through 2011, obtained from the U.S. Department of Energy (n.d.).

Internet usage is by the World Bank (2019). It represents the number of Internet users per 100 people and accounts for the influence of the Internet over the years 1990 through 2011.

Distance measures the kilometer distance tourists had to travel between countries, with values obtained from the Distance Calculator (n.d.). Distance between the capital cities of countries was used; however, like many other prior researchers, I use New York, rather than Washington for the U.S., since more trading goes through New York.

RTA is the variable for regional trade agreements and measures trade blocs. For example, it captures membership in the European Union and EFTA. RTA takes a value of 1 for EFTA, 2 for the EU, 3 for NAFTA, and 4 for “NONE” (countries not having membership in EFTA, EU, or NAFTA) (EFTA, 2012; NAFTA, 2012; EU, 2012).

English is a dummy variable, taking the value of 1 if English is the dominant language in a country, otherwise, taking the value of 0. The list of English-dominant countries is from Sheffield University (2019).

Christianity is a variable accounting for the Christian religion and represents the 2010 ratio of Protestant Christians in a particular country’s population (Association of Religion Data Archives, n.d.).

The Law variable indicates the ease of doing business in countries, and countries were ranked from 1 to 190, where a lower numerical value represents a more favorable business environment (1 = most business-friendly regulations). The research used the 2016 values of the index with each country having a specific numeral value (World Bank, 2019).

Hofstede’s cultural dimensions (power distance, individualism, masculinity, uncertainty, and orientation) are from Hofstede (1991, 2001).

3. Estimation results

Table 1 shows the regression estimates for Equation (1)(1) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_{4}Oi{l}_{j,t}+{\beta }_{5}Interne{t}_{i,t}+{\text{Ψ}}_{ij,t}.$(1) and Equation (2)(2) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_4\ln \left(Distanc{e}_{ij}\right)+{\beta }_{5}Oi{l}_{j,t}+{\beta }_{6}Interne{t}_{i,t}+{\varsigma }_{ij,t}.$(2) . First, we see the effects of the traditional gravity model specification on tourism, showing how the GDP of the departing country and the arrival country impacts tourism. The wealth of the departing country had significant positive effects on tourism, and the arrival country’s GDP was insignificant or slightly significant. Distance between the countries negatively affects tourism. Based on the sample used here running from 2003 through 2016, VAT increase has a negative impact on tourism, so a higher VAT did not affect the marginal increase of foreign tourists negatively. The research does not find oil price increase to have a significant effect on foreign tourist arrival. In addition, for remote countries, many have believed the Internet to have much impact on tourism, and I find the Internet to have a positive effect on tourism, although not always significant.

Table 1. Estimation of Equation (1)(1) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_{4}Oi{l}_{j,t}+{\beta }_{5}Interne{t}_{i,t}+{\text{Ψ}}_{ij,t}.$(1) and Equation (2(2) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_4\ln \left(Distanc{e}_{ij}\right)+{\beta }_{5}Oi{l}_{j,t}+{\beta }_{6}Interne{t}_{i,t}+{\varsigma }_{ij,t}.$(2) )

Regressors	Equation (1)(1) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_{4}Oi{l}_{j,t}+{\beta }_{5}Interne{t}_{i,t}+{\text{Ψ}}_{ij,t}.$(1)	Equation (2)(2) $\ln \left(Tourist{s}_{ij,t}\right)={\beta }_0+{\beta }_{1}VA{T}_{j,t}+{\beta }_2\ln \left(GDP\text{\_}hom{e}_{j,t}\right)+{\beta }_3\ln \left(GDP\text{\_}hos{t}_{j,t}\right)+{\beta }_4\ln \left(Distanc{e}_{ij}\right)+{\beta }_{5}Oi{l}_{j,t}+{\beta }_{6}Interne{t}_{i,t}+{\varsigma }_{ij,t}.$(2)
	$ln\left(Tourist{s}_{ij,t}\right)$	$ln\left(Tourist{s}_{ij,t}\right)$
$ln\left(GDP\mathrm{\_}ot{h}_{j,t}\right)$	.488*** (9.68)	.365*** (11.03)
$ln\left(GDP\mathrm{\_}Ic{e}_{j,t}\right)$	−.404 (−0.57)	.788* (1.74)
$ln\left(Distanc{e}_{ij}\right)$		−2.549*** (−11.45)
$VA{T}_{j,t}$	.054*** (8.15)	.057*** (13.72)
$Oi{l}_{j,t}$	−.002 (−0.74)	.001 (0.52)
$Interne{t}_{i,t}$	.031*** (8.83)	.003 (0.94)
$Constant$	4.379 (0.69)	16.409*** (4.03)
R-sq	0.7442	0.9023
Obs.	88	88

More specifically t-statistics marked *** is signifcant at 1% level, t-statistics marked ** is signifcant at 5% level, and t-statistics marked * is signifcant at 10% level.

Table 2 presents the estimation results for Equations (3)(3) $ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}RT{A}_{i,t}+{\omega }_{3}Englis{h}_{i,t}+{\omega }_{4}Christianit{y}_{i,t}+{\omega }_{5}La{w}_{i,t}+{\xi }_{i,t}.$(3) and (4(4) $\begin{array}{rl}& ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}Distanc{e}_{ij}+{\omega }_{3}RT{A}_{i,t}+{\omega }_{4}Englis{h}_{i,t}+{\omega }_{5}Christianit{y}_{i,t}\\ & +{\omega }_{6}La{w}_{i,t}+{\omega }_{7}Pow\mathrm{\_}Di{s}_j+{\omega }_{8}In{d}_j+{\omega }_{9}Ma{s}_j+{\omega }_{10}Unce{r}_j+{\omega }_{11}Or{i}_j+{\xi }_{i,t}\end{array}$(4) ) with visiting tourists as the dependent variable. The research does not find an increase in the VAT in the hospitality industry to have a significant negative impact on a marginal increase in foreign visiting tourists (presented with a logarithmic treatment of the dependent variable). Second, the effects of Hofstede’s cultural dimensions indicated that only uncertainty (Uncer) and individualism (Ind) had a positive impact on tourism inflow. Hofstede’s other dimensions of power distance (Distance), masculinity (Mas), and orientation (Ori) have a negative impact on visiting tourism. Taken together, this indicates that cultural differences can indeed have negative impacts on marginal changes (estimated in logs) in tourism.

Table 2. Estimation of Equation (3)(3) $ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}RT{A}_{i,t}+{\omega }_{3}Englis{h}_{i,t}+{\omega }_{4}Christianit{y}_{i,t}+{\omega }_{5}La{w}_{i,t}+{\xi }_{i,t}.$(3) and Equation (4(4) $\begin{array}{rl}& ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}Distanc{e}_{ij}+{\omega }_{3}RT{A}_{i,t}+{\omega }_{4}Englis{h}_{i,t}+{\omega }_{5}Christianit{y}_{i,t}\\ & +{\omega }_{6}La{w}_{i,t}+{\omega }_{7}Pow\mathrm{\_}Di{s}_j+{\omega }_{8}In{d}_j+{\omega }_{9}Ma{s}_j+{\omega }_{10}Unce{r}_j+{\omega }_{11}Or{i}_j+{\xi }_{i,t}\end{array}$(4) )

Regressors	Equation (3)(3) $ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}RT{A}_{i,t}+{\omega }_{3}Englis{h}_{i,t}+{\omega }_{4}Christianit{y}_{i,t}+{\omega }_{5}La{w}_{i,t}+{\xi }_{i,t}.$(3)	Equation (4)(4) $\begin{array}{rl}& ln\left(Tourist{s}_{ij,t}\right)={\omega }_0+{\omega }_{1}VA{T}_{j,t}+{\omega }_{2}Distanc{e}_{ij}+{\omega }_{3}RT{A}_{i,t}+{\omega }_{4}Englis{h}_{i,t}+{\omega }_{5}Christianit{y}_{i,t}\\ & +{\omega }_{6}La{w}_{i,t}+{\omega }_{7}Pow\mathrm{\_}Di{s}_j+{\omega }_{8}In{d}_j+{\omega }_{9}Ma{s}_j+{\omega }_{10}Unce{r}_j+{\omega }_{11}Or{i}_j+{\xi }_{i,t}\end{array}$(4)
	$ln\left(Tourist{s}_{ij,t}\right)$	$ln\left(Tourist{s}_{ij,t}\right)$
$VA{T}_{j,t}$	.049*** (5.71)	−.006 (−0.45)
$Pow\mathrm{\_}Di{s}_j$		−.014* (−1.83)
$In{d}_j$		.163*** (7.21)
$Ma{s}_j$		−.018*** (−2.82)
$Unce{r}_j$		.0499*** (4.84)
$Or{i}_j$		−.025*** (−5.11)
$RT{A}_{i,t}$	.733*** (4.54)	1.356*** (7.23)
$Englis{h}_{i,t}$	−.471** (−2.14)	−3.588*** (−8.05)
$Christianit{y}_{i,t}$	−2.069*** (−7.27)	−4.619*** (−5.82)
$La{w}_{i,t}$	−.054*** (−8.38)	−.237*** (−6.52)
$Distanc{e}_{ij}$		.004*** (4.43)
$Constant$	10.503*** (32.68)	−5.218** (−2.08)
R-sq	0.7253	0.9075
Obs	99	99

Robust t-statistics reported in parentheses. ∗∗∗, ∗∗, and ∗ are significant at the 1%, 5%, and 10% levels, respectively.

The research results show that the membership in RTA does have significant positive effects on visiting travelers, so tourists from common trade blocs were more likely to visit. Also, the variable measuring the use of the English language does have a negative impact on tourism, probably because the native language of Iceland is not English. Christianity, the native religion of Iceland, does have a negative impact on tourism inflow as was the Law system and the Distance tourists needed to travel. The origins of the legal system in Iceland are based on the Danish legal system; however, it is subjected to European Law through the European Economic Area. Finally, it is not surprising that distance has a negative impact on visits of foreign tourists since Iceland is an island in the North Atlantic far from all countries and continents.

4. Summary and conclusions

Tourism is a growing industry, challenging governments on how best to manage the inflow of tourists and requiring infrastructure provisions from them. Therefore, it is important for governments to gain clearer understanding of how other factors affect tourism, when managing tourism and be aware if a VAT increase is realistic for infrastructure financing. This is particularly important for the Northern European countries, in need of improved infrastructure to manage the increase in tourism, with Iceland being a case country in this research.

The wealth of the tourist home country has positive effects on increasing tourist visits - indicating that wealthier tourists are more likely to visit, however, travelling distance has negative effects - making tourists less eager to visit the farther distance. Other factors estimated included Internet access and the cost of oil. Higher oil prices did not affect tourists’ willingness to visit the country; however, better Internet access had positive effects on tourism. Moreover, having to cross trade blocs when visiting the country has a negative impact on visiting tourists.

Culture differences, Christianity as a religion, English as a language, and the legal system generally have a negative impact on tourist inflow, indicating that tourist background matters.

The main results indicate that tax increase has no impact on the willingness of tourists to visit; however, the wealth of the home country and better Internet access helps in attracting new tourists, but higher international oil price - reflecting higher travelling cost -does not impact tourist inflow. Moreover, the host country can expect distance and differences in culture, language, and religion to make tourists less interested in visiting.

The results, based on the dataset running from 2003 through 2016, suggest that a VAT increase does not influence the willingness of foreign tourists to visit. Future research could analyze if the reason is that VAT increases and oil prices have less impact on wealthier tourists. This study examines the raw number of tourists. Future studies could analyse if there is a difference in this respect, based on the demographics of tourists.

Foreign visitors pay the bills in the tourism industry, for the most part, and thereby pay the value added tax (VAT) on tourism. This is the case in small economies like Iceland with unusually high ratio of foreign tourists to the local population. In this respect, tax increase in the tourism industry may be a feasible option for governments, if paid by foreigners - rather than the local voting population.

Author statement

Dr Helga Kristjánsdóttir did research at the University of Copenhagen, Denmark, during 2000–2004, gaining valuable research connections with European researchers when she participated in a research and training network funded by the European Commission, titled: “Analysis of International Capital Markets: Understanding Europe’s Role in the Global Economy”.

Before obtaining her doctoral degree, Kristjánsdóttir formed research connections and understanding of the European system, when allocated in Belgium, while completing her master studies in economics in Leuven, Belgium. Prior to the stay in Belgium, Kristjánsdóttir also formed research connections in the US and gained a valuable understanding of the American economic system during the time she finished her 2-year MBA studies in Boston, in the USA.

Dr Kristjánsdóttir has research cooperation with international researchers and has twice organized the Nordic International Trade Seminars (NOITS) teaming together with Nordic researchers.

Dr Helga Kristjánsdóttir’s areas of interest are in the broad field of business and economics and include international trade & investment, and renewable energy, as well as the tourism industry and business organizations.

Correction

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The author received no direct funding for this research.

Notes on contributors

Helga Kristjánsdóttir

Helga Kristjánsdóttir is an Associate Professor at the University of Akureyri. She completed an MBA from Boston College USA in 1995, an MS degree in Economics from the Katholieke Universiteit Leuven Belgium in 2000, and a Ph.D. in Economics from the University of Iceland in 2004. During her Ph.D. studies, she worked as a researcher at the Department of Economics at Copenhagen University, at the Centre for Applied Microeconometrics (CAM), and at the Economic Policy Research Unit (EPRU). Dr Kristjánsdóttir has worked as an economist and researcher as well as a stockbroker and in management consultancy. Her teaching experience includes classes in international economics, international business, statistics, and energy economics at undergraduate and graduate levels. Working experience includes teaching at the University of Akureyri, Bifröst University, and the University of Iceland.