Multilevel Approaches and the Firm‐Agglomeration Ambiguity in Economic Growth Studies

Oort, Frank van; Burger, Martijn; Knoben, Joris; Raspe, Otto

doi:10.1002/9781118427248.ch6

Cited by 25 publications

(54 citation statements)

References 82 publications

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“…Similar results were recently provided by Van Oort et al . (), who studied the effects of agglomeration economies on firm survival and employment growth at the city level in the Netherlands, a spatial level that is much lower than the presently employed NUTS 2 level. Van Oort et al .…”

Section: Resultsmentioning

confidence: 99%

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Firm Profitability and Agglomeration Economies: An Elusive Relationship

Stavropoulos

Skuras

2015

Tijd voor Econ & Soc Geog

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Recent empirical research has questioned the ability of agglomeration economies to stimulate profitability and healthy financial performance in firms. We devise a cross-sectional sample of approximately 410,000 firms that were active in all subsectors of the manufacturing industry and that were located across 191 NUTS 2 regions of 15 European Union member states in 2005. For each firm, we calculate two profitability indicators and a labour efficiency indicator. We find that the part of the variance of the profitability and labour efficiency indicators that is attributed to regions is very small. Furthermore, fitted multilevel models show that the quantitative effect of regional specialisation, despite being statistically significant, is very small. The results are robust across more refined geographical scales and subsectors. However, the NUTS 2 level remains the major spatial scale of the design and implementation of European Union regional policy. Our results benefit from the power and safety of a large sample and challenge conventional approaches to agglomeration research and cluster policy.

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Section: Resultsmentioning

confidence: 99%

“…Van Oort et al . () partitioned the variance of survival and employment growth in regional, sectoral, and cross‐classified regional‐sectoral levels and found that regions do not explain more than 3–5 per cent of the total variance, while between‐firm variance retained more than 90 per cent of the total variance in all analyses.…”

Section: Resultsmentioning

confidence: 99%

Firm Profitability and Agglomeration Economies: An Elusive Relationship

Stavropoulos

Skuras

2015

Tijd voor Econ & Soc Geog

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“…We also note that explicitly introducing regional information in the model of the unobservable effectively leads to introducing the advantages of multilevel modeling in our estimation algorithm (e.g., Van Oort et al. ).…”

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confidence: 99%

“…We also attempted multilevel regression analysis to cast light on the effects of the agglomeration forces on TFP following Van Oort et al. (). We estimated an equation with dependent variable our TFP measure and containing as explanatory variables firm‐level, regional‐level, and cross‐level interaction terms for each category of our three regional typologies.…”

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confidence: 99%

Regional disparities and productivity in China: Evidence from manufacturing micro data

Rizov¹,

Zhang²

2014

Papers in Regional Science

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Abstract. In this paper we first estimate firm-specific total factor productivities within 2-digit manufacturing industries using a semi-parametric algorithm and micro data for the period 2000-2007. Next, to characterize regional disparities in China we compute aggregate productivity by the categories of three regional typologies, based on population density, coastal-inland, and rural-urban criteria. We analyse the productivity differentials across the categories of the typologies by decomposing regional productivity level and growth into productivity effect and industry composition effect. We find clear evidence of regional convergence. Besides density of economic activity, recent policy and structural factors seem to affect regional productivity level and growth differentials. JEL classification: D24, O49, R11, R30Key words: Productivity, regional disparities, inequality, convergence, China, micro data IntroductionRegional disparities in China have been widely studied in recent years, both in terms of economic growth (e.g., McMillan et al. 1989; Lin 1992;Rozelle et al. 1998; Fan et al. 2003; Meng and Wang, 2005)

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“…Along these lines, it is also unknown which networks are relatively more important for urban development (trade, knowledge, or corporate). Using a multilevel framework (see Van Oort et al., ), it is possible to analyze to what extent the performance of firms is dependent on their location in global networks.…”

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confidence: 99%