ArticleEntrepreneurship Recovery in Romania after the GreatRecession. A Dynamic Spatial Panel ApproachZizi Goschin 1,2,*, Mihai Antonia 1 and Horia Tigau 1Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies,010552 Bucharest, Romania; [email protected] (M.A.); [email protected] (H.T.)2 Institute of National Economy, 050711 Bucharest, Romania* Correspondence: [email protected]: Goschin, Z.; Antonia, M.;Tigau, H. EntrepreneurshipRecovery in Romania after the GreatRecession. A Dynamic Spatial PanelApproach. Sustainability 2021, 13,10702. Entrepreneurship plays a key role in transforming the economy and society by stimulatingeconomic development, testing innovative ideas, creating new jobs, and by enriching the quality oflife and human existence. Entrepreneurship dynamics depend upon a series of local and nationaleconomic factors, but are also affected by the international environment, such as the current COVID19 pandemic. Statistical data show that new businesses are created at a slower rate during an economic crisis, when the economic climate is harsh, and business opportunities are scarce. Nevertheless, there are local differences in the reaction to crises, and new business formation tends to declinewith variable intensity from one region to another, even in the same country. The crises are actingas a trigger for some opportunity-driven entrepreneurs, and resilient regions can thrive even intimes of crisis or recover faster after a depression. To capture spatial interactions, as well as spatialshort- and long-term effects, the method employed in our analysis relies on the estimation of dynamic spatial panel models. We tested the potential impact of a large variety of social and economicindicators on the creation of new firms and found that the most consequential factors of influenceare the economic crisis (expressed through a binary variable), GDP per capita, FDI per capita, inflation, unemployment, and education. Our results convey a powerful policy message for both national and regional decision makers. We believe that, while putting entrepreneurial initiative to thetest, the current COVID-19 crisis might act as a catalyst that leads to innovation and reshapes theeconomy and society.Keywords: economic crisis; entrepreneurship; new firms; resilience; spatial panel data modelAcademic Editor: Sajid AnwarReceived: 8 September 2021Accepted: 23 September 2021Published: 26 September 2021Publisher’s Note: MDPI stays neutral with regard to jurisdictionalclaims in published maps and institutional affiliations.Copyright: 2021 by the authors. Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( IntroductionEntrepreneurship is an essential ingredient for regional development and competitiveness, and understanding its underlying factors is a matter of high interest for scholarsand policy makers alike. A wealth of economic literature has studied entrepreneurship inrelation to economic crises [1–3], as well as including locational factors of influence. Theterritorial distribution of entrepreneurial activity in any country is largely shaped by thespecific local economic, social, and political climates in which these firms perform theiractivity. Economic shocks might exert a powerful, yet territorially uneven influence onthe birth of new firms and the survival of existing ones. Some regions can be more resilientthan others to economic shocks, therefore the entrepreneurial initiative is less affected bythe economic crises [4]. However, all regions are impacted to a certain degree when amajor recession occurs, such as the one triggered by the 2007–2009 global economic crisis.During economic crises, new firms, which are generally smaller and more vulnerable, are less likely to survive and thrive. Their survival rate is influenced not only by thesize and sector of activity, but also by the location [5,6]. In this context, an important factorin understanding the regional differences in the recovery from a crisis is the spatial dependence that exists among neighboring regions. Spatial dependence is represented bySustainability 2021, 13, 10702. urnal/sustainability

Sustainability 2021, 13, 107022 of 12similar characteristics of neighboring regions from a geographic point of view. It impliesthat neighboring regions tend to be alike, i.e., their characteristics are usually positivelycorrelated. Given the scarcity of studies that acknowledge spatial dependence while modelling entrepreneurship activity (e.g., [4,5,7]), we aim to fill a gap in the literature by analyzing entrepreneurship recovery and dynamics after a crisis from a spatial perspective,using appropriate spatial econometrics tools.Starting from the previous considerations, this paper addresses several researchquestions: how did entrepreneurship recover after the Great Recession that occurred between 2007 and 2009? What are the main regional factors of influence? Does location matter and are there spatial spillover effects between regions? We answer these questions byapplying up-to-date spatial econometrics tools on relevant regional data, using Romaniaas a case study. Romania is one of the largest ex-socialist countries in Central and EasternEurope and benefited greatly from the transition to the market economy. Entrepreneurship, virtually nonexistent prior to the collapse of the communist regime in 1989, flourished and became a driver for the general economic growth of the country. Sharing manysimilarities with the other former socialist countries in the region, Romania can be a relevant example for the progress of entrepreneurship and recovery after a major economiccrisis in a post-communist economy.The crises act as a trigger for some opportunity-driven entrepreneurs, and resilientregions can thrive even in these conditions or recover faster after the depression. Giventhe scarcity of regional statistical data regarding the economic effects of the COVID-19pandemic, we draw lessons from the previous major crisis, namely the 2007–2009 GreatRecession, for assessing the likely economic effects of the current crisis on the birth of newfirm. We focus on the interval between 2008 and 2020, aiming to investigate the impact ofa major economic crisis on new business formation in Romania, and to determine if theresponse to crises is shaped by location. This research extends the empirical debate in [8]on the determinants of new business formation in Romania.2. Literature ReviewPrevious research indicated that besides their contribution to economic growth, newfirms are also able to enhance economic resilience to crises [2,3]. Some studies showed thatregions with a high level of entrepreneurship are more flexible and more resilient to exogenous shocks due to increased economic diversification and the entrepreneurs’ abilityto perceive and exploit potential opportunities even in times of crisis [9]. Recent academicdebates on new firm formation during the last economic crisis showed that regions withhigh entrepreneurial initiative are better at withstanding crises and can adapt faster tonew economic conditions [10]. Resilience to economic crises is frequently linked to entrepreneurship in the literature, and the findings reveal that entrepreneurship contributes tourban resilience [11], wage cuts may relatively influence entrepreneurial initiative [12],and the “spatial stickiness” of the “entrepreneurial regimes” promote resilience and theability to adapt to economic shocks [10].Entrepreneurial initiative, embodied in new firm formation, represents an importantdriver of economic development, which has captured the interest of many researcherstrying to better understand its determinants. Numerous studies that empirically investigated the factors that influence new firm formation [10,13–24] obtained different results,depending on the period or the geographic localization of the study. Previous researchrevealed many regional factors affecting the dynamics of entrepreneurial activity, such aspopulation growth, demographic characteristics, economic growth, wages, unemployment, and entrepreneurial density [14,20,25,26].

Sustainability 2021, 13, 107023 of 122.1. Economic GrowthThere is a growing body of literature identifying the determinants of new businessformation on a regional basis [14,21,23,27]. Choosing the location for a new firm dependson the presence of agglomeration economies, especially in cities where population andfirm density can influence the search costs for workforce and suppliers [28].A common determinant of new firm creation in literature is economic growth. A positive relation between GDP per capita and entrepreneurship was found in several studies[29,30], while others indicated negative correlations in the case of poor countries [31].There are also studies arguing that GPD per capita is not significant for new firm creation[25].Increases in wages trigger greater demand for goods, which positively influences thecreation of new firms [28]. High wages, associated with a high level of skills, can stimulatethe creation of new firms, since new entrepreneurs are usually better skilled than the average population [21].2.2. UnemploymentHigher rates of unemployment in a region could lead to more people starting theirown businesses, due to difficulties in finding a job [8]. Many studies investigating unemployment and its relationship with new business formation seem to be contradictory anddependent on time or geographical factors [8,18]. In the short term, the relationship isnegative—an increase in unemployment predicts, for instance, a decrease in entrepreneurial activity in the following months, explained by difficulties at the level of the national economy and social aid for the unemployed. In the long term, the relationship ispositive, with an increase in unemployment predicting higher entrepreneurial activity,which may be explained by the “push effect”. Higher rates of unemployment could leadto new firm formation, as a negative change in labor market conditions, and the limitedavailability of waged employment, may push individuals into entrepreneurial activity.2.3. EducationEducation as a factor of influence on entrepreneurship, is explained in the literaturebased on human capital theory: people invest in themselves through education becausethey expect a higher income [32] or they want to acquire the necessary skills to validateprofitable business opportunities [10]. Higher education positively influences laborproductivity, which ensures entrepreneurial success. As a determinant of new firm formation, education (especially tertiary education), was found to be statistically significantin numerous empirical studies [20,33,34]. Since the results depend on location and time,there are also studies that did not find education to be statistically significant for the birthof new enterprises [13,16].2.4. Demographic CharacteristicsAmong other factors of influence, demographic characteristics, such as the age distribution of the population, were found to be surprisingly significant for the creation ofnew enterprises. It is common knowledge that the working population in the 35–50 agerange is more likely to start a business [16,35]. A study in the Netherlands [35] showedthat the impact of population changes on the birth rates of new firms depended on theregional context: it is negative in urban areas and positive in rural ones.2.5. InflationStart-ups are often financed with entrepreneurs’ own savings, which, in an inflationist economic environment, puts the entrepreneurs at higher risks, due to the increaseddifficulty of recovering the initial investments [36] and the disruptions in business plans.Studies have found a negative correlation between inflation and entrepreneurship [37],confirming that unpredictability discourages long-term involvement in a business.

Sustainability 2021, 13, 107024 of 123. Econometric Model, Variables, and DataAn economic crisis hitting a region will likely influence the economic performance inneighboring regions as well. It implies that spatial dependence, which exists among neighboring regions, needs to be accounted for in the econometric model [38–41]. Consequently,our study uses spatial econometrics to describe both spatial and temporal dependencieson entrepreneurship data, more precisely on the entrepreneurial initiative in Romania.Aiming to investigate all possible autocorrelations in our data, the investigationstarts with a general nesting spatial model [42–44]:Y W Y X β W X θ µ γ ε(1)with ε λ W ε vwhere in our case, Y is the number of new firms created in county i at time t, X arethe regressors, k is for the explanatory variables, W is a binary contiguity queen-type matrix that describes spatial relations among counties, ρ denotes the response parameter ofthe dependent variable lagged in space, W X stands for the explanatory variables klagged in space, and W Y is the dependent variable lagged in space. Finally, µ is a vector of spatially fixed effects, γ is time fixed effects. β and θ represent response parameters of the exogenous explanatory variables, ε represents the spatial errors, λ is the spatial autocorrelation coefficient, and v are the spatialy uncorrelated errors.Starting from the general nesting spatial model described above, we can reduce it tosome several more restrictive models [45] as presented in the following, Table 1:Table 1. Typology of spatial models.ModelSpatial autoregressive model with autoregressive errors(SAC)Spatial Durbin model (SDM)Spatial autoregressive model (SAR)Spatial error model (SEM)Restrictions Spatial Lagθθ 0WY, Wuλ 0θ 0 and λ 0θ 0 and ρ 0WY, WXWYWuFurthermore,