The regional variations of entrepreneurial dynamism: a mixed methods study

ABSTRACT

Given that added knowledge and deeper understanding are needed with regard to regional variations in the creation of new firms, this study seeks to answer the following two research questions: What are the variables that explain entrepreneurial dynamism and how may they be apprehended under the four necessary and complementary dimensions of this phenomenon, namely the demand, supply, institutional and spatial dimensions? And how should the nature and interrelatedness of these dimensions and their associated variables influence regional policymakers and other regional stakeholders in their efforts to stimulate entrepreneurship in their region? In order to do so, we used mixed methods to collect and analyze regional data, first doing a regression analysis of quantitative data on 97 small regions in Canada’s province of Québec, followed by a qualitative survey of regional stakeholders on eight matched pairs of regions. A phenomenological qualitative analysis was then effectuated in order to gain a deeper understanding of the research variables’ effects and thus grasp the complex socio-economic reality of entrepreneurial dynamism in a region. The results of the study confirm the importance and interrelatedness of the four dimensions of entrepreneurial dynamism in providing new insights into these questions. Moreover, the findings that results from these quantitative, qualitative and holistic analyses have implications for the policies of regional authorities and for the actions of other regional stakeholders.     

Traces of the Iron Curtain: A multivariate analysis of regional cohesion in Europe

The present study aims to test relative welfare differences among regions in Europe, so as to examine whether the post-communist era has led to more socio-economic cohesion in Europe. The performance of European regions is analysed, compared, and assessed by using the Regional Competitiveness Index (RCI) and stylised fixed nominal categories. The current status of regional cohesion is tested on the basis of detailed data on 268 NUTS 2 European regions by using a robust methodology oriented towards univariate comparison of location parameters, multivariate classification by the decision tree and CHAID algorithm, and comparison of nominal variables with four values based on density plots.Multivariate classification appears to offer statistically excellent results with an overall correct prediction rate for post-socialist and capitalist regions in Europe of 99.6%. The research results from the Higher education and Innovation pillars, reveal a convergence of capitalist and post-socialist regions with capital cities and a divergence of regions with administrative capitals and other regions. Relatively, the two groups which perform best are both groups with capitals, while the group of capitalist regions with a capital city is significantly better in almost all pillars.The key message is that the transition of post-socialist regions is not yet over. Capitalist regions in Europe perform better than post-socialist regions in eight of the nine pillars of regional competitiveness. Our research results also reveal that the group of post-socialist regions without capital cities are significantly lagging behind the rest of the regions in Europe, and thus form the most vulnerable group of European regions. As there is data continuity in the official RCI classification and measurement, policy makers will be able to compare the performance of their own regions over time and to design appropriate concerted strategies accordingly. From this perspective, our study draws several interesting lessons and results for policy makers at various levels. Place-based regional planning and policy based on our analysis framework may be helpful in developing effective measures to cope with the socio-economic legacy of the “Iron Curtain” and get closer to regional cohesion in Europe.     

Youth labour market performances in the Russian and Italian regions

The focus of this paper is on youth unemployment in Italy and Russia: in both countries, youth unemployment rates (YURs) are higher than adult (or total) ones. Despite these general trends, there are significant regional differences in YURs and above-average YUR regions tend to cluster close to each other. Moreover, a distinction between “North” and “South” regions seems appropriate for both countries. The purpose of this study is to identify key determinants of YURs in the Russian and Italian regions, for the period 2000–2009. We also search for the existence of distance spatial effects. In particular, we estimate a modified Arellano–Bond model for the regional YUR, including some explanatory and control variables (e.g. regional GDP in PPP, regional population density, regional total unemployment rate), together with year dummies and North/South dummies. The use of distance matrixes enables important analysis to be conducted on the role played by spatial effects, which turn out to be significant. Also the negative impact of the 2008–2009 crisis is statistically confirmed (at least in the case of Italy). The relevant policy implications are highlighted in the conclusions.     

Index Based Regional Analysis: The Case of the Former Soviet Union and Russia

This paper presents a methodology for analysing inter-regional differences and identifying a suitable combination of policies for a set of regions. The methodology is based on the development of a composite index and is applied to compare (i) the members of the Former Soviet Union (FSU) and (ii) the regions of Russia. All variables considered and incorporated in the relevant index are (1) scaled from 0–100, so that the index is independent of units of measurement, and (2) weighted using survey results. According to the adapted regional development index Lithuania is on the top of the ranking followed by Latvia, Estonia, Ukraine, Belarus, Georgia, Russia, Armenia, Moldova, Azerbaijan, Kazakhstan, Uzbekistan, Turkmenistan, Kyrgyzstan, and Tajikistan. The FSU countries are positioned on a regional development index – per capita income mapping to investigate whether emphasis should be placed on regional, environmental or sustainable development policies. Finally, an index that incorporates various socioeconomic components is computed for the regions of Russia which are subsequently classified based on the value of this index. This classification shows that the regions with the best index values are in the Central–Southern part of the country (with the exception of Sackha Republic, which is in the West). The regions with the lower index values are in the Western part of the country and in parts of Central Russia (Mariel republic, Moldovia Republic, Perm region).     

Understanding Russian regions’ economic performance during periods of decline and growth—An extreme bound analysis approach

This article uses “extreme-bound”-type analysis to revisit the determinants behind the widely differing economic growth in Russian regions prior to the recent global financial crisis. Using data of regional growth in 1995–2006 for 77 Russian regions, it examines the growth drivers for the phase of economic decline up to 1998 and for the period of strong growth afterwards separately. Looking at forty variables considered to be potentially related to growth, it determines, for each of the two periods, the ones robustly associated with Russian economic performance. Among the variables considered are proxies of politico-institutional features, indicators of economic reform, and measurements of both economic and non-economic initial conditions. The main findings are as follows: during the period of economic decline up to 1998, differences in Russian regional growth were almost entirely driven by initial conditions, with resource and human capital endowments, industrial structure, and geographical location playing the dominant roles. However, after the 1998 crisis, the importance of initial conditions declined and was basically reduced to fuel production, advantageous geographical location, and population structure. There is also some evidence that more reform-oriented policies and better regional leadership made a difference. These results could be seen as pointing to determinants of economic performance in periods of actual economic decline being different from those in normal times of economic growth.     

Forecasting macroeconomic variables using disaggregate survey data

We construct factor models based on disaggregate survey data for forecasting national aggregate macroeconomic variables. Our methodology applies regional and sectoral factor models to Norges Bank’s regional survey and to the Swedish Business Tendency Survey. The analysis identifies which of the pieces of information extracted from the individual regions in Norges Bank’s survey and the sectors for the two surveys perform particularly well at forecasting different variables at various horizons. The results show that several factor models beat an autoregressive benchmark in forecasting inflation and the unemployment rate. However, the factor models are most successful at forecasting GDP growth. Forecast combinations using the past performances of regional and sectoral factor models yield the most accurate forecasts in the majority of the cases.     

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.     

International trade,integration and industrial location: The case of Germany

The paper confronts empirical results on the spatial distribution of integration effects and export activities in the FRG with prediction based on different theoretical approaches. It is proved that integration has at most very slightly favoured the higher agglomerated regions, and has not been to the detriment of the periphery. Export activities contributed to regional industrial despecialization and to decreasing interregional disparities. Population potentials, calculated with different distance parameters, regional productivity, the sectoral composition of industry, and average firm size are tested as explanatory variables. The results question that there are contemporary effective ‘regional’ determinants of integration effects.     

Topography and spatial population dualism in the People's Republic of China (1933-1990)

"Looking at half a century of available data, a sharp spatial dualism is observed in the regional population distribution of the People's Republic of China. The vast share of the PRC's population is located in the Eastern and South-Eastern regions. Two topographical variables related to accessibility, distance from the eastern seaboard and elevation, seem to be at the core of this dualism. Their isolated and combined effects upon the spatial distribution of the PRC's population are examined for the period 1933-1990. It is documented that the population concentration in certain regions of the PRC is not so much because of their proximity to the seaboard, but because of their low elevation, especially in the eastern part of the nation. Also documented is a result indicating that in time the combined effects of these impedances on the regional population distribution in the PRC is linearly declining."     

DETERMINING MINIMUM WAGES IN CHINA: DO ECONOMIC FACTORS DOMINATE?

We analyze the determinants of minimum wages in China at the regional level. We include a broad set of economic variables and consider the role of spatial spillovers, which reflect the geographical pattern of regions and can arise for several reasons, including competition between local policymakers. The analysis primarily reveals the existence of strong regional ties in the development of minimum wages. Once these spatial effects are considered, the role of economic variables in the determination of minimum wages declines, and their impact is lower than initially thought. Whereas consumption per capita and consumer prices remain significant, regular wages lose their importance when controlling for reverse causation. Although minimum wage regulation stresses the relevance of economic factors in the determination of appropriate levels, actual development is largely driven by regional dependencies. As minimum wage standards set by local officials do not fully reflect regional economic conditions, further reform should be on the agenda.     

Measuring regional efficiency: A method tested on the fabricated metal products industry in Sweden, 1973–1975

This paper presents a method of measuring the efficiency of regions as production environments of manufacturing industries. The approach is a rather general view of the firm in a market economy. The functions which the firms must perform are discussed. From that, hypotheses are made regarding the elements of the environment which should constitute the regional production milieu and thus influence the efficiency of the firms. By way of factor analysis the original variables are reduced to seven regional factors, which are put into productivity functions where their parameters are estimated. From those parameters indexes of regional efficiency are calculated.     

Multi-modal,multi-output,multiregional variable input-output model

A multi-modal, multi-output, multiregional variable input-output (MMMVIO) model is introduced to evaluate the economic impact of a transportation system. The MMVIO model differs from the conventional input-output models by being price and cost sensitive. The regional technical coefficients, trade coefficients, modal choice of shipment, input mix and output composition are determined by the price and cost variables, a property not shared by the conventional input-output models.The transportation system reduces shipping cost of delivering commodities between regions, thereby stimulating economy of trading regions. The MMMVIO model captures the development impact incident to the transportation system.     

Industrial clusters,flagship enterprises and regional innovation

ABSTRACT

For a sample of all 88 counties in the State of Ohio over a 5-year period, this study documents the effect of flagship enterprises and concentrated industrial clusters on regional innovation. Consistent with the agglomeration arguments and the knowledge spillover theory of entrepreneurship, both appear to affect regional innovation positively. Additionally, regional educational attainment positively moderates the effect of industrial clusters on innovation. At the same time, flagship enterprises primarily affect regional innovation in regions with low education levels. Results are obtained with the help of conservative econometric techniques and are robust to the choice of alternative dependent variables and estimators. The findings have major policy implications and provide insights into alternative routes to encouraging regional innovation.     

Entrepreneurship and regional competitiveness: The role and progression of policy

Regions have gained a position at the forefront of the economic development policy agenda. However, the regional approach to economic strategy remains contested. This paper tests the extent to which regional policy in less competitive regions is accounting for issues relating to entrepreneurship and enterprise development as a tool for improving regional competitiveness. It does so by examining policies undertaken by the UK Labour government 1997–2010, drawing on interviews with policy makers and an analysis of relevant policy documents. This paper finds that entrepreneurship policy at the regional level is multidimensional, with policies broadly ranging from those that are either economically or socially driven. Although there is a considerable policy activity in these areas across less competitive regions, enterprise policy making remains relatively undifferentiated across the regions. There are a number of evolutions in regional policy occurring, especially a shift from policies relating to the facilitation of clusters to those focused on developing regional innovation ecosystems. It is found that regional policy makers are under pressure to measure short-term outputs at the expense of long-term nurturing. The paper also finds that there is a tension between using enterprise policy as a tool for improving regional competitiveness or for addressing economic and social disadvantage.     

INVESTMENT PATTERNS AND THE COMPETITIVENESS OF GREEK REGIONS

This paper aims at mapping and analyzing the determinants of industrial activity in Greek regions in order to assess current investment patterns. For this purpose, we estimate a conditional logit model of 226 new established firms for 1996 and 1997. Results give interesting insights that are likely of particular importance to regional policy makers. Noteworthy is the spatial concentration of firms in different prefectures while the large metropolitan cities, Athens and Thessalonica, although with declining shares, prevail as the dominant hosts. European regional policy seems to enhance firms'entry via its effect on economic development variables, in contrast with the Greek Development Law, which turns out non-influential.     

Spatial econometric analysis of spatial general equilibrium

A structural spatial econometric model for nine regions of Israel is estimated using non-stationary spatial panel data during 1987–2015. The model focuses on the relation between regional markets in labour, housing and capital when there is imperfect internal migration between regions, when capital is imperfectly mobile between regions, and when building contractors operate across regions. Since the regional panel data are non-stationary, the econometric methodology is based on spatial panel cointegration. The estimated model is used to simulate the temporal and spatial propagation of regional shocks induced, for example, by regional policy (land for housing, regional investment grants). Impulse responses are temporally and spatially state dependent. They are also highly persistent because of longevity in housing and capital.     

Measuring and forecasting retail trade in real time using card transactional data

We build big data retail trade indicators for Spain using high-dimensional card transaction data from one of the country’s biggest banks. The resulting indicators replicate the dynamics of the Spanish retail trade indices (RTI), regional RTIs (Spain’s autonomous regions), and RTI by retailer type (distribution classes) released by the Spanish National Statistics Institute. The new indicators not only have a higher frequency (daily data) and higher geographical and sectorial breakdown but are also shown to improve nowcasting and forecasting power for the official RTI, making them key variables to monitor consumption.     

Regional dimensions of factor and fuel substitution in U.S. manufacturing

This paper analyzes the regional responses to price increases in U.S. manufacturing in the form of fuel and factor substitution. A translog specification of a production process with eight inputs organized into a two stage optimization process — optimizing the mix of four fuels that constitute the energy input and then optimizing the input mix of physical capital, working capital, labor and aggregate energy — is used. Sectoral and regional variations in factor and fuel substitutions as evident from econometric estimation of the model at the level of 50 states and four census regions are discussed and interpreted.     

Assessment of development regions for financial support allocation with fuzzy decision making: A case of Turkey

European Union is a project focused on the balanced distribution of the prosperity, established by the common market, to all regions. For this purpose, in order to collect comparable statistics, socio-economic zones have been established within the framework of certain criteria using the classification of Nomenclature of Territorial Units for Statistics (NUTS). These regions are formed in 3 levels, based on the countries that are members and candidates for membership. Supports provided within the framework of the EU in order to reduce regional socio-economic disparities and to ensure regional development are being made and measured on the basis of regions (development zones) established with Level 2 NUTS. As a candidate country to the EU, Turkey also tries to achieve harmonization and regional development through Instrument for Pre-Accession Assistance (IPA). In this study, the extent to which the development regions identified in the Turkish scale should benefit from such supports is assessed on the basis of specific criteria. How to distribute IPA support, which is a limited resource, to the regions according to framework agreements and regional development goals is a complex issue. In order to solve this problem, development zones are evaluated using two different Multi Criteria Decision Making methods: Fuzzy-PROMETHEE and Fuzzy-MULTIMOORA. As a result, a framework to provide specific distribution of funds to support regional development and to show the weaknesses of these regions is presented.     

Performance of cultural heritage institutions: A regional perspective

Most studies on performance evaluation in the cultural sector are based on the efficiency assessment of a network of institutions. Nevertheless, very few works take territorial divisions as the case study. Under this approach, we design a spatial production function which merges several cultural resources in order to optimize the impact of a regional system of cultural institutions in terms of cultural production and use of services provided. The aim of this paper is therefore to evaluate the efficiency of cultural heritage institutions in Spain from a regional perspective. We take regional networks of museums and libraries as emblematic case studies over a long period, from 2002 to 2020. We first apply a dynamic-network DEA model to measure efficiency, which allows the production function to be divided into stages and time intervals, considering inter-reliant inputs between production phases and time lapses. We also apply truncated regression models to study the effect of external variables on regional cultural efficiency, especially those related to socioeconomic conditions in regions, the scope of the cultural and tourist sector, and institutional indicators. Results show that regional cultural efficiency depends on the level of training and on the demographic structure rather than on economic wealth. Differences are also found between the goals of cultural production and cultural consumption (visitor impact). These findings might prove useful for policy implications regarding resource allocation vis-à-vis defining and accomplishing cultural purposes at a regional scale, and also for revealing causes of inefficiency with a view to improving quality in institutions –which ultimately drives economic development.