Location Quotients Research Articles

A Modification of the Cross-Industry Location Quotient for Projecting Sub-Territorial Input-Output Tables

Economic accounts at sub-territorial level are projected primarily through Location Quotients (LQ). The degrees of sectoral specialisation at this level will therefore be key in spatial projections. This article advocates rectified use of the Cross-Industry Location Quotient (CILQ). Indirectly, the aim is to check to what extent CILQs are well exploited, given that they are the fundamental reference in other techniques. The input-output (IO) tables for the Euro 19 Area for 2010 and 2015 are taken as a reference for analysis purposes. A statistic is used to measure the degree of similarity between the accounting frameworks of ten countries in the Euro Area and their projections using CILQ, Flegg's formula, its augmented version, and the CILQ variant.

Who can walk? An analysis of public amenity access in America’s ten largest cities

How uneven is the proximity to public amenities like libraries and schools among racial groups, or children and older people? This paper uses a catchment area approach to evaluate walkable proximity to four common public amenities (parks, libraries, schools, and transit stops), looking at four racial categories and a set of variables that one might reasonably expect proximity to be related to (e.g., population density). For each of the 10 largest US cities examined, location quotients for each amenity (libraries, parks, schools, and transit stops) were calculated at three distances (0.25 miles, 0.5 miles, and 1 mile). Across all amenities, the racial group whose LQ had the greatest increase when comparing net median change between distance bands (i.e., between .25 miles and 1 mile) was Black Americans. There were large differences between the location quotient means and medians in non-White racial groups for each amenity, indicating a large amount of skew. In most cities and with most amenities, the difference between mean and median was considerably smaller in White populations, indicating a more normal curve and fewer outliers. Proximity, in other words, seems to be more homogenous in White populations. The LQs were also significantly higher in White populations across cities. Further, in all cities except Los Angeles, Asian populations were generally the most under-represented group for each catchment area around each amenity. The fact that non-White residents predominantly had lower LQs and therefore lower access (with some exceptions, for example, in the case of schools) is a generalized and problematic finding that adds to the body of evidence documenting the spatial injustices that American cities continue to manifest.

The Industrial Pattern of Italian Regions: A Disaggregated Sectoral Analysis Based on Input–Output Tables

Italy joined the so-called ‘Industry 4.0’ European framework in 2016, which designed and approved a national plan to regulate this key issue for regional development. To better support such a framework, the present study attempts to quantify the contribution of the Italian regions to the output formation process. More specifically, a multi-sectoral Input–Output (IO) model that supports national policies was proposed to cumulatively consider 29 industries that partition the Italian economy into representative branches at the level of administrative regions. Elementary input data were derived from the inter-sectoral table of the economy released by the Italian National Institute of Statistics (ISTAT). The economic outcomes of the Italian regions were estimated using a non-survey procedure, based on Flegg Location Quotients, to determine the upstream and downstream positions of each industry at country and regional levels. Indices grounded on the Hypothetical Extraction Method (HEM) further delineated the role each industry plays in the regional economy. The empirical findings of this study demonstrate how non-survey IO regionalization and the resulting industry-based indices provide appropriate knowledge for regional development policies.

Discussing the Spatial Underpinnings of Tourism Policy and Planning in Romania

"The paper examines the spatial concepts and mechanisms that drive the reconfiguration of the tourism space and provide policy-relevant informa tion. Mapping the spatial patterns of tourism supply and demand at finely-grained data over the last two decades, the analysis employs spatiotemporal and scaling methods to capture the interactions and de pendencies among tourism concentrations. The findings point to space-tourism realignments based on heterogeneous concentration patterns and trajectories of change, supply growth and ex pansion at the first level of contiguity, and diffused domestic vs. polarized international arrivals. The bi nary approach of tourism concentrations of supply and demand with varying location quotients enables the identification of both differences and similarities in terms of contextual and tourism development in dicators. In support of context-sensitive policy inter ventions, we argue that space should be regarded as a central dimension of the tourism development pol icy. Providing a snapshot of the tourism concentra tions in 2019, the study may count as a baseline ref erence for further analyses in post-pandemic times."

The spatial and temporal resilience of the tourism and outdoor recreation industries in the United States throughout the COVID-19 pandemic

Accurately quantifying industry resilience is essential to devising effective recovery strategies. Previous research into industry resilience has either quantified the concept with single metrics aggregated across large geographies (e.g., visitation) or used metrics comparing the relative concentration of an industry within a region to the national average (e.g., location quotients). The former set of metrics prohibits spatially targeted recovery efforts while the latter fails during national crises. We propose the measurement of tourism and outdoor recreation industry resilience to COVID-19 based on growth rates in employment, wages, and establishments using publicly accessible time-series data on all counties in the United States. We use these indicators to characterize the spatio-temporal patterns of industry resilience across the country. The indicators can serve as a useful reference for diagnosing and monitoring industry resilience as well as developing targeted policies, programs, and promotion efforts that facilitate more localized response efforts.

The value of data visualisation: tracking geographies of informal care in Ireland, 2002–16

As policy and funding associated with informal/unpaid/family caring develops, more attention has been given to data that support and inform such policy. In particular, evidence around aspects of inequality is often expressed in geographical variations between places in terms of numbers and rates. In general, to date, research on informal caring has focused little on how such variations can be visualised and analysed. This short article looks at the mapping of data from Irish censuses between 2002 and 2016 to: first, explore and visualise patterns of caring, including high-intensity caring. A second broad aim is to use different spatial techniques, including location quotients and clustering, to provide more robust visualisations of spatial variations. Finally, some putative links are but forward between the variable geographical distributions of caring and changes in legislation and policy for carers in Ireland during that same period.

A new proposal to model regional input–output structures using location quotients. An application to Korean and Spanish regions

AbstractThis paper is based on the use of Flegg's location quotients (FLQ) and proposes a novel procedure for the estimation of the unknown parameter δ in regions with and without input–output frame availability. Applied to data for the Korean regions for the year 2015, firstly the determination of the optimal δ is addressed by solving a general optimization problem and, secondly, a regression equation is proposed to estimate the value of δ from the explanatory variables of interregional road freight transport (IRFT) and imports from the rest of the world (IROW). The results obtained show a lower bias in regard to the true values of the regional inputs coefficients in relation to other methods based on location quotients.

Regional and dynamic specialization of beef production in Mexico (2000-2018)

Objective: To determine the growth, specialization, and dynamics of beef carcass production in eight regions of Mexico, in the 2000-2018 period. Design/Methodology/Approach: The annual growth rates from 2000 to 2018 in each of the regions were calculated. Based on this information, we were able to determine the relative and dynamic specialization of beef production through Regional Analysis Techniques, such as the Location Quotient and the Differential-Structural Method. Results: During the 2000-2018 period, the domestic beef carcass production had diverse annual growth. Most of the location quotients greater than the unit were obtained in Chiapas and Sonora, while Sinaloa and Chihuahua obtained lower location quotients. The results of the Differential-Structural Method showed that Sinaloa was the most dynamic region, while Veracruz and Sonora have been left behind and showed little specialization in all sub-periods. Limitations/Implications: The differentiated annual growth between regions implied underdevelopment and intra-regional dynamism over time. The change in the productive calling of some regions involved a transformation from being specialized to non-specialized. The dynamics of the regions was determined by hypothetical gains, while the underdevelopment was related to hypothetical losses of various magnitudes. Findings/Conclusions: Sinaloa had the highest growth and dynamism of all the regions. Veracruz and Sonora were left behind and showed little specialization throughout the analyzed period.

Territorial servitisation in Italian industrial districts: the role of technological and professional KIBS

PurposeThis paper aims to analyse to what extent Italian industrial districts (IDs), with their traditional manufacturing specialization, experimented a territorial servitisation process in terms of spread of specifically professional and technological knowledge-intensive business services’ activities over the period 2012–2018.Design/methodology/approachThis paper articulates knowledge-intensive business services activities in two types, technological knowledge-intensive business services and professional knowledge-intensive business services. It tracks their growth and their co-location with manufacturing sectors in Italian IDs by means of firm employment data and location quotients. Firm employment data is extracted from Statistical Archive of Active firms (ASIA) data set provided by Italian National Institute for Statistics (ISTAT). ASIA data is matched with ISTAT territorial identification of Italian local labour systems and IDs.FindingsIn 2018, Italian IDs featured, next to their traditional over-specialisation in manufacturing activities, an under-specialisation in knowledge-intensive business services’ activities. Nevertheless, the dynamic analysis carried out over the period 2012–2018 shows that IDs firm employment in technological knowledge-intensive business services and professional knowledge-intensive business services grew at a higher rate than the national average.Originality/valueThe novelty of this paper is to distinguish between technological knowledge-intensive business services and professional knowledge-intensive business services and to measure the presence and the growth of these two different types of knowledge-intensive business services in Italian IDs.

LIFECYCLE CARBON FOOTPRINT: THE CASE STUDY OF THE ELECTRICITY USE IN PUEBLA, MEXICO

Greenhouse gas emissions inventories and carbon footprints assessed at the local level are critical for any country, mainly for those countries which are part of the Paris Agreement such as Mexico, where federal and local governments join forces to design climate-change mitigation policies. However, determining carbon footprints is time and resource-intensive and not always possible for local governments. To meet this need, we propose an alternative method using lifecycle input-output analysis and location quotients to quantify direct and total emissions of the Mexican state of Puebla caused by its use of electricity during 2013. We quantify the emissions from the production and consumption-based perspective, finding that Puebla’s economy emitted a total of 15 million metric tons of CO2e caused by industrial sectors’ electricity use, which represented 3 % of the total national emissions caused by Mexico’s industrial electricity use. The most significant contributors to Puebla’s total greenhouse gas emissions were the “food and beverage preparation services” and the “business support services” sectors accounting for 38 % and 9 % of Puebla’s total emissions and 50 % and 23 % of direct emissions, respectively. We conclude that, in addition to the decarbonization of the energy matrix, potential climate change mitigation policies should reduce the intensity factors of the sectors with the highest emissions identified with the proposed method.

Spotting Error Patterns in Input–Output Projections Using Location Quotients

The Sustainable Development Goals (SDGs) stated by the United Nations (UN) constitute a universal agenda committed to human rights. In this context, mathematics can perform a fundamental role. Exploring possible contributions to these goals could be considered an interesting approach. Input–output (IO) tables provide detailed information for socio-economic quantifications. Thus, they allow for more precise policy decision-making and application in the SDG strategy. However, the smaller the subnational unit to be considered, the less statistical information that is available. Survey-based IO tables with large product/industry disaggregation are seldom published. Therefore, non-survey methods to estimate subnational IO tables based on the national are needed. These methodologies should yield optimal results. In the present investigation, different formulations for these non-survey regionalization methods are analyzed. The work focuses on the methodologies based on location quotients (LQ). As a result, some error patterns associated with current formulations present in literature are described. A slight refinement of these methodologies is proposed in order to improve the estimation’s accuracy.

Industrial Agglomeration Analysis for Local Economic Growth (Case Study Medium-Large Industries at North Sumatera)

The ideas for creating share value have been shown to improve economic performance. In this study, we aim to map the Location Quotients of Medium-Large Industries (IBS) agglomeration in North Sumatra and show how industrial agglomeration affects local economic growth and company performance. In this study, we use Location Quotients (LQ) index to measure the agglomeration of Medium-Large Industries (IBS) by district or city. The measurements were carried out in 34 regencies and cities in North Sumatra between 2017 and 2019. The results show that IBS agglomeration increased by 20.59% in 2017 and a steady increase by 23.53% in 2018 to 2019. The added value of this study is the expansion of the dominant logic co-creation concept, with the principle of industrial agglomeration able to assist companies in achieving sustainability and competitive advantage by promoting the creation of shared value, ranging from planning corporate resources to meeting the economic value for all stakeholders.

Gendered dimensions of educational premium disadvantage in earnings in USA, 2019.

The relationships between gender-based earnings disparity and gendered dimensions of human capital gains and labor market changes are quite complex. Some scholars have argued that gender bias improves the over economy of a country/society. Others, however, have argued otherwise, adding to the narrative that despite an overall positive role of educational/human capital gains by women, the benefits reaped by them is non-linear, often with declining premiums for educational progress. This research investigates gendered earnings disadvantage and (dis)parity across US counties by employing GIS-based maps, descriptive statistics, correlations and regression analyses wherein female earnings and female-versus-male earnings ratios are regressed against select explanatory variables representing educational attainments, gender-based work-status, and their occupational over/under-representation in the labor market. Five-years estimates data (2015–2019) from the NHGIS are used for computing location quotients for major occupation-types by gender and additional statistical analyses. Females with professional, Master’s and doctoral degrees have improved earnings, even though gender parity is better for both genders among the less educated. Sadly, gender disparity in earnings is higher when male-versus-female ratio increases for those majoring in science/engineering, science and engineering-related and business degrees. Greater gender parity, however, is noted when more men major in Education—a sub-field largely deemed as feminine. This research calls for focused policy interventions toward encouraging more women in STEM and science/engineering disciplines, along with strategic programs to help attract more women into working full-time—one of the several ways toward bridging the earnings gap.

Effects of the concentration of manufacturing industry on Croatian regional growth

Spatial concentration of economic activity is a phenomenon that has important implications for the development potential of the local, regional and national economy. This statement stems from two facts: first, there is a tendency of people and economic activity to concentrate in major cities and regions; and second, similar and connected companies sometimes agglomerate together at a particular location to take advantages of the external economies. This paper examines the effects of spatial concentration of manufacturing industry on Croatian regional growth. The industrial concentration (especially of the manufacturing sector) improves competitiveness among firms, enhances knowledge spillovers and increases the demand for labor and industrial products, leading ultimately to potentially higher growth rates. To examine the effects of concentration of manufacturing industry on Croatian regional growth, a panel analysis is conducted combining spatial (21 Croatian counties) and time (16 time periods) dimensions. The best way to measure concentration is by using the location formula to calculate location quotients weather on the basis of employment or gross value added. Therefore, the location quotients are independent variables of interest in the model whereas GDP, GDP p.c. and Gross value added of manufacturing put, regional economic prosperity and industrial output, respectively. Based on the results of the panel analysis it can be concluded that manufacturing industry is still an important factor of regional growth in Croatia, although its relative significance in Croatian economy is continuously declining over the last two decades.

A regionalized IO-model to value seasonal recreational ecosystem services in a mountain National Park in Spain

Recreational Ecosystem Services (RES) are among the most frequently evaluated ecosystem services. RES are seen as a major opportunity for sustainable development in areas of high ecological value resulting from the presence of emblematic species, habitats or scenery, often integrated in conservation areas, in particular in mountain areas affected by depopulation, rising environmental risks and poverty. Economically, the assessment of RES has been based on Contingent Valuation and Choice Experiments, methods with limitations related to their subjectivity. Alternatively, Input-Output (IO) models provide a very accurate and effective way of valuation of RES with regional information regarding interindustry transactions. Whilst data on nature tourist expenditure may be only available annually, tourism inflows have a strong seasonal behavior, which impacts the profitability of several local economic activities. In this paper, we firstly constructed a novel regionalized IO-model based on Cross-Industry Location Quotients using employment data and, secondly, based on Monte Carlo simulation, we estimated nature tourist expenditure monthly using data on nature tourism inflows. This method allowed for a more precise RES evaluation, estimating direct, indirect and induced monthly economic impacts of nature-based tourism. The method was applied to the Ordesa and Monte Perdido (OMP) National Park in the Spanish Pyrenees. To estimate the average tourist expenditure, we collected and analyzed spending on commerce, hospitality and restaurants, leisure, and transport of 385 visitors. Results suggest that using a regionalized IO model leads to a considerable reduction of over-estimation of the economic impact of tourist expenditure estimated by conventional methods. Taking into consideration the direct, indirect and induced effects of tourist expenditure in 2016–2018, the total annual output effect in the OMP National Park amounted to €208.8 million, while the total income effect amounted to €86.29 million. Also, a total of 2,429 jobs were created which indicates that for each thousand annual visitors to the National Park, 3.8 jobs are created in the surrounding area. Overall, the proposed methodology can be easily applied to the remaining National Parks in Spain or other regions in the world, making it a valuable tool to estimate the value of RES in areas affects by strong seasonality, to set priorities and support regional policies for mountain sustainable development.

Urban Shrinkage and Socio-Economic Segregation in Medium-Sized Cities: The Case of Schwerin (Germany)

AbstractAlthough past studies have found that processes of urban shrinkage may act as a catalyst for socio-economic segregation, these relationships remain underexplored outside the context of large cities and capitals. Moreover, cities at lower-tiers of the urban hierarchy in post-socialist Europe have been doubly excluded from the critical discourse on the socio-spatial effects of shrinkage. Hence, this article examines how shrinkage affects socio-economic segregation in the medium-sized post-socialist city of Schwerin, employing segregation indices to assess levels of spatial unevenness and location quotients to map intra-urban patterns of vulnerable population groups over time. Results indicate processes of shrinkage may exacerbate socio-economic segregation in medium-sized cities and that the spatial heterogeneity of shrinkage intersects with uneven distributions of affluence and poverty. However, suggesting that legacies of state socialism shape contemporary socio-spatial change, segregation in Schwerin is strongly conditioned by its socialist-era housing estates, which are generally characterised by the highest rates of population decline, vacancy, and vulnerable groups.

Agglomerating or dispersing? Spatial effects of high-speed trains on regional tourism economies

Following the paradigm of New Economic Geography, this study examines the impact of high-speed train (HST) services on the spatial structure of regional tourism economies in China. We collect panel data of 286 Chinese cities from 2007 to 2016 and adopt tourism-revenue location quotients to measure the relative agglomeration level of tourism economies for a city. According to the estimation results, tourism economies tend to agglomerate from the cities outside the HST network to those inside the network. Also, tourism economies start to disperse among cities within the network as more HST services become available. Furthermore, the results unveil the spatial heterogeneity of HST impacts. The moderating effects exerted by other transport modes are examined as well. Lastly, implications are provided for policy-makers and stakeholders on how to internalize the benefits from HST networks on tourism development.

Construction of Truncated Input–Output Tables for Russian Regions Using Location Quotients

Construction of Truncated Input–Output Tables for Russian Regions Using Location Quotients

Changing employment subcenters and opportunity in the Pittsburgh metropolitan area

ABSTRACT Urban structure reflects land use processes and affects the livability of metropolitan areas. Structure and process can be illuminated by analysis of employment subcenters whose delineation often utilizes density and threshold criteria modified by local knowledge. This study addresses two questions: (1) are employment subcenters thus defined differently from the metropolitan area as a whole and (2) are employment subcenters different from each other? Employment density thresholds and totals are analyzed at census block group level of geography. Location quotients for subcenters and subcenter components (census block groups) are analyzed using Mann-Whitney rank order tests. The results indicate that the answer is “yes” to both questions. Affirmation of the first supports the credibility of density/threshold delineations, and of the second indicates an under-studied aspect of urban structure. Subcenter differences may contribute to problems of worker accessibility to employment opportunities. The results suggest that unstable urban structure may be an impediment to socioeconomic mobility and that, on a theoretical level, it may be desirable to revisit the question of whether influence fields are discrete or probabilistic.

The Pitfalls of Using Location Quotients to Identify Clusters and Represent Industry Specialization in Small Regions

<ns3:p>This paper examines the use of location quotients, a measure of regional business activity relative to the national benchmark, as an indicator of sectoral agglomeration in small cities and towns, and as a measure of industry specialization that might impact the number of new business startups in these places. Using establishment-level data on businesses located in Maine, our findings suggest that the addition of one "hypothetical" establishment in very small towns leads to a dramatic change in the magnitude of the region-industry location quotient. At population sizes of about 4,100 or more people, however, location quotients are reasonably stable. Regression results from an analysis of the relationship between new business activity and regional industry specialization show that the effect of location quotients on business startups switches from "inelastic" to "elastic" at a population size cutoff of about 2,600 residents. Overall, our findings suggest that researchers and practitioners should exercise caution when using location quotients to study small regions.</ns3:p>