scholarly journals What drives spatial clusters of entrepreneurship in China? Evidence from economic census data

2017 ◽  
Vol 46 ◽  
pp. 229-248 ◽  
Author(s):  
Liang Zheng ◽  
Zhong Zhao
Keyword(s):  
Census Data ◽  
Spatial Clusters ◽  
Economic Census

scholarly journals The Impact of the Capture of Leaders of Criminal Organizations on the Labor Market: Evidence from Mexico

2021 ◽  
Author(s):  
Daniel Osuna Gómez ◽  
Keyword(s):  
Labor Market ◽  
Census Data ◽  
Negative Impact ◽  
Difference Analysis ◽  
Criminal Organizations ◽  
Before And After ◽  
Economic Census ◽  
The Difference ◽  
Integral Assessment ◽  
The Impact

This paper estimates the impact of the capture of leaders of criminal organizations on the labor market in municipalities where these organizations operated between 2004 and 2006. The difference-in-difference analysis compares different employment outcomes in cartel locations and the rest, before and after the capture of cartel leaders. The results show that captures caused a decrease in nominal wages and paid employment in cartel municipalities. Using Economic Census Data, I find that captures also caused a fall in the number of establishments and had a negative impact on other establishment outcomes. This document focuses exclusively on the impact of the capture of leaders of criminal organizations on the labor market until 2011 without studying other possible consequences, and thus does not make an integral assessment of this policy

Empirical Research on China's Regional Economic Distribution and Characteristics

2011 ◽  
Vol 204-210 ◽  
pp. 350-353
Author(s):  
Xiao Guang Lu ◽  
Jian Qun Zhu ◽  
Meng Ying Fan
Keyword(s):  
Division Of Labor ◽  
Empirical Research ◽  
Regional Economy ◽  
Census Data ◽  
Jiangsu Province ◽  
Regional Economic ◽  
The Past ◽  
Model Based ◽  
Economic Census ◽  
Economic Regions

According to the second economic census data of Jiangsu Province, this paper firstly uses PCA-HCA model based on provincial cities data to classify economic regions. And then, it uses BLR-HCA model to reclassify the economic regions based on counties data. Finally, it comes to the conclusion that the past regional classification ways of Jiangsu Province need to be updated. The research on regional economy is dynamic and timely, while deepening the division of labor and finance is an effective way to develop Jiangsu’s regional economy.

A longitudinal study of changes in intra-metropolitan employment concentration in Beijing: Decentralisation, reconcentration and polycentrification

Urban Studies ◽  
2019 ◽  
Vol 57 (4) ◽  
pp. 748-765
Author(s):  
Tieshan Sun
Keyword(s):  
Metropolitan Area ◽  
Census Data ◽  
Urban Structure ◽  
Spatial Trend ◽  
Urban Core ◽  
Spatial Changes ◽  
Economic Census ◽  
Service Jobs ◽  
Beijing Metropolitan Area ◽  
Longitudinal Dataset

This article explores the spatial trend of intra-metropolitan employment concentration in the Beijing metropolitan area from 2004 to 2013. We use multiple-year economic census data and construct a unique longitudinal dataset of employment at the subdistrict level, applying the locally weighted regression method to identify employment centres in Beijing. The results show that jobs continued to decentralise from the urban core to the suburbs in Beijing over the studied period; however, different from the common trajectory of Western metropolitan spatial evolution, decentralised jobs tended to be more concentrated in subcentres and the polycentric urban structure prevailed in Beijing. Polycentricity strengthened in Beijing from 2004 to 2008, but job dispersion increased at the expense of polycentricity during 2008–2013. However, job dispersion did not follow an unstructured model; instead, subcentres played an increasingly important role in structuring the dispersed jobs. Job dispersion in Beijing has been more associated with the scatteration of service jobs, while manufacturing jobs tended to be more concentrated in subcentres, which contributed to the polycentric development of the capital. We also observe the persistence in the location of employment centres in Beijing over the studied period, as well as substantial spatial changes in the boundaries of employment centres, which suggests that the employment concentrations within the metropolitan area are persistent but not static.

scholarly journals Are Knowledge-Intensive Services an Urban Growth Factor in the Global Periphery? (Un)Fulfilled Possibilities in the Large Metropolitan Areas of Mexico

Urban Science ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 58
Author(s):  
Boris Graizbord ◽  
Luis Enrique Santiago
Keyword(s):  
Growth Factor ◽  
Growth Performance ◽  
Labor Productivity ◽  
Urban Growth ◽  
Census Data ◽  
Metropolitan Areas ◽  
Service Economy ◽  
Spatial Logic ◽  
Economic Census ◽  
Knowledge Intensive

In this paper, we analyze the labor productivity of “knowledge-intensive services” (KIS) located in the four larger metropolitan areas in Mexico. We discuss the accepted explanation to why big cities concentrate the best and most qualified jobs and activities that generate innovative and technological change and therefore labor productivity. In Mexico this is the case for some knowledge-intensive sectors, but some paradoxes emerge when services are disaggregated by analytical, synthetic, and symbolic categories. We use disaggregated economic census data for 2004 and 2014 to find changes in labor productivity in those KIS sectors compared to the metropolitan service economy. In fact, we can identify different spatial logic according to the type of knowledge that KIS produce. Results show unexpected paradoxes in terms of type of KIS category viz a viz their location and growth performance in the four larger metropolitan areas.

Entrepreneurial Supply among the Underprivileged in an Underdeveloped Region- A Case Study of Odisha

2015 ◽  
Vol 2 (1) ◽  
pp. 32-52 ◽  
Author(s):  
Shiba C. Panda ◽  
Janmejoy Khuntia
Keyword(s):  
Entrepreneurial Orientation ◽  
Census Data ◽  
Economic Factors ◽  
Economic Background ◽  
Economic Census ◽  
Back Ground ◽  
Underdeveloped Region ◽  
Social Marginality ◽  
Socio Economic Factors

The socio-economic factors such as the economic background of members, their affiliations to social sub-groups, cultural back ground, business ethics, inter alia influence the supply of entrepreneurship in a particular region. Moreover, absence of social marginality in an underdeveloped region acts as a hindrance to entrepreneurial behavior. Odisha is such a backward region in India which has exhibited some sign of entrepreneurial orientation among social groups as revealed from MSME and Economic Census data. The present study aims at examining the nature of entrepreneurship of this region.

scholarly journals What Happens When Firms Patent? New Evidence from U.S. Economic Census Data

2011 ◽  
Vol 93 (1) ◽  
pp. 126-146 ◽  
Author(s):  
Natarajan Balasubramanian ◽  
Jagadeesh Sivadasan
Keyword(s):  
Census Data ◽  
Economic Census ◽  
New Evidence
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