AuthorChirca, Andrei
  1. Introduction

    In March 2020, due to the ongoing pandemic of the coronavirus disease 2019 (COVID-19), universities across Romania suspended face-to-face instruction. Most academic activities moved online, most important activities--teaching and students' interaction with the professors and the administrative staff--being carried on exclusively online. This unprecedented situation cancelled students' on-site presence at the university, and so the need for the students to live in the university city has also become optional.

    The absence of students from the university city becomes visible where usually the ratio of students to city residents is high. In Romania, the largest university centers are Bucharest, Cluj-Napoca, Iasi, and Timisoara, however the highest ratio of students to residents is in Cluj-Napoca (Figure 1).

    In terms of economic impact, the visitors of students enrolled at Babes-Bolyai University alone spent an estimated 7.5 million Euros in the city of Cluj-Napoca in the year 2015 (Chirca and Lazar, 2019). And since only 9.3% of those visitors spent a night in a hotel or hostel during their stay in Cluj-Napoca, the type of tourism they perform remains unexplored and mostly untraceable in the official tourism data (Chirca and Lazar, 2019).

    The university has a significant impact on the economic life of its host city: a large number of people who are not residents shop locally, salaries are paid to academics, a significant number of students from other places decide to stay after graduating becoming city residents (Pastor, Perez and de Guevara, 2013). In economic impact studies, these are known as short-term and demand-side effects. As a large-scale consumer of inputs such as labor, goods and services, and generator of outputs: skills, know-how, and local attractiveness, the university is a major factor in metropolitan economic development (Felsenstein, 1996, p. 1566).

    Therefore, estimating students' expenditure is subject to universities' local economic impact studies. It is also explored in studies on the economic struggle to obtain higher education or simply on the cost of living for students. The complexity of the economic impact of the universities has on one hand generated a diversity of economic impact studies, but on the other hand discouraged such attempts (Pellenbarg, 2005). Studies linking university spending to the local economy can be traced back to 1949 (Florax, 1992): Tully, A.M., 'The Economic Contribution of Rutgers University to the Welfare of the City of New Brunswick during the Fiscal Year 1947-1948'.

    Compared to the results of a survey conducted in 2016 to measure the expenditure of the Babes-Bolyai University (BBU) students in 2015, we can estimate a gap in the local economy of Cluj-Napoca caused by one month of coronavirus (COVID-19) pandemic quarantine in 2020, as the quarantine completely changed the ways in which the university functions. For that, the students' expenditure assessed for 2015 was adjusted with the annual inflation rate, with the number of BBU students enrolled in January 2020 (a total of 31,570), and with the total number of students studying in all universities in Cluj-Napoca.

    The paper consists of three sections. The next section explores the conceptual aspects of some studies on economic impact of universities in which student expenditure issues are analyzed. The third section presents the methodology and the main results of the survey carried out among BBU students to assess their expenditure in the reference year 2015 as part of a broader study on the BBU impact on the local economy of Cluj-Napoca. Finally, the estimations of BBU student expenditure are adjusted to quantify total student expenditure in Cluj-Napoca for one month in 2020.

  2. Theoretical framework

    Universities leave marks on the local community, some of them tangible, others intangible, overt or covert as they are caused by factors both internal and external to the academic environment (Chirca and Lazar, 2018). Warsh (2006) argues that it is enough to look at any map to observe that cities hosting universities have remained on top or reinvented themselves after decline, inferring that knowledge is a powerful factor of production. The implications of hosting a major university campus by a community, such as the economic value and contribution of the university and its impact on the socio-economic development of the community are well-discussed in the literature (Armstrong, 1993; Bleaney et al., 1992; Blackwell, Cobb and Weinberg, 2002; OECD, 2007; Pastor, Perez and de Guevara, 2013; Schubert and Kroll, 2016).

    Universities, the traditional providers of human resources and knowledge, are critical socio-economic development actors (Dzisah and Etzkowitz, 2008, p. 101). Etzkowitz (2008) places universities in the Triple Helix (university-industry --government)--an interaction that is key to innovation in an increasingly knowledge-based society. Universities are assigned the role of catalysts of local and regional economy development increasingly more often (Steinnes, 1987).

    Considerable efforts to understand the contributions of universities to the functioning of regional economies can be found in regional studies focused on their roles (Drucker and Goldstein, 2007; Goldstein and Renault, 2004; Florax, 1992). The 2011 EU Guide 'Connecting Universities to Regional Growth' calls for an active engagement of public authorities to involve universities in cooperation with research centers, businesses and other civil society actors, in regional innovation strategies for smart specialization (Hahn and Vassiliou, 2011).

    Due to the rapid growth of the higher education sector in the United States in the 1960s, the first official methodology to research the local impact of a university on income and employment appeared in 1971. Caffey and Isaacs (1971) designed it for the American Council on Education as a template methodology to quantify the short-term economic impact on local economy of the demand-side effects--the economic impact in a certain year (or fiscal year) of the university and its related spending.

    More than twenty years later, Goldstein, Maier and Lueger (1995) proposed eight distinctive university outputs that can have an impact on economic development. Such varied and complex outputs of the higher education led to numerous discussions either on improving the ACE methodology (Bluestone, 1993; Brown and Heaney, 1997; Elliott, Levin and Meisel, 1988), or on creating a better classification of the impact (Beck et al., 1995; Leslie and Slaughter, 1992), or even on proposing a different methodology, such as the Ryan short cut method (Ryan and Malgieri, 1981).

    Schubert and Kroll (2016) summarized the complexity of the university factors of impact as inputs, outputs, first order effects and second order effects. The clear distinction between long-term, knowledge-based supply-side, and the short-term, expenditure-based demand-side, of the same inputs is very helpful (Figure 2) because they allow for a complex and nuanced assessment of the economic contribution of higher education institutions.

    Siegfried, Sanderson and McHenry (2007) examined 138 studies covering 241 institutions and presented their reliability limitations: the selection of multipliers for indirect and induced impacts; the measuring methods they used, double counting of data, as well as unclear counterfactual scenarios and delimitation of the areas of impact.

    More recently in Europe, Pastor, Perez and de Guevara (2013) improved Caffrey and Isaacs' methodology by adding stochastic processes for assumptions with uncertainty. Thus, by using the requirements specified by Siegfried, Sanderson and McHenry (2007), the methodology based on Monte Carlo simulations allows for a clearer estimation of students' expenditure through a survey design that distinguishes between students based...

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