Relationship between city size and firm productivity – A new interpretation using the Chinese experience

This paper contributes to the literature on the relationship between city size and firm productivity by focusing on agglomeration, selection (market competition), and sorting (presence of firms with diverse productivity) effects using Chinese firm-level data for 1998–2013. Contrary to the existing literature, our parametric regression estimates from nearly two million firms show that when the selection effect is controlled, productivity advantage in big cities is reversed. This outcome is explained through a quantile regression showing the existence of left-sided sorting (inefficient firms sort themselves to larger cities) in big cities which is not captured in existing empirical literature. We further find that (1) left-sided sorting is stronger in exporters than non-exporters; (2) is also generated mainly in enterprises with high asset-liability ratios; and (3) selection has a positive effect on firm productivity, suggesting that market competition is key in an explanation of the rapid growth of big cities in China.     

TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration

This article estimates agglomeration effects via calculating EG (Elilsion & Glaeser) and TFP growth (Total Factor Production) by considering the undesired output of the industrial enterprise database and the entropy weight method. Using panel data of 207 county-level cities in China and 28 two-digit manufacturing industries from 2003 to 2013 based on SIC codes, this paper analyzes the relationship between agglomeration and TFP growth through the smooth transition model under different regions and factor-intensity. The results are as follows. (1) A negative relationship appears in manufacturing productivity. The agglomeration effect changes to the crowded effect. Environmental pollution is also generated by transportation and inadequate pollution treatment technology. (2) The excessive agglomeration phenomenon of developed areas (eastern region) is less than the less developed areas (central and western regions). (3) Resource-intensity industries present two thresholds that indicate complex regional features. For various intensive industries in different regions, the relationship between GML and agglomeration is different. High agglomeration does not always promote TFP growth. (4) At different levels of urban industrial agglomeration, the influences of efficiency change and technical change on GML are different. Overall, moderate agglomeration in all regions helps promote economic development.     

Agglomeration economies and university program creation in the knowledge economy

Existing academic literature on the relationship between agglomeration economies and university activities is both under-theorized and relatively sparse in terms of empirical examination. This paper addresses each of these voids by contributing and analyzing a market model of pro-revenue education program creation such as graduate-level executive business education (e.g. EMBA) that reveals some intriguing characteristics. For instance, it shows that demand for these pro-revenue programs is inelastic and therefore uniquely determines their availability. More specifically, we show that through agglomeration economies these types of education programs are more likely to emanate from universities located in metropolitan areas and from less academically prestigious universities. Regression analysis of a cross-section of national public universities lends support to important facets of our formal model by suggesting that agglomeration economies continue to increase the probability of offering EMBA programs through a city size of approximately 2.12 million and that the probability that a given business school will offer an EMBA is negatively related to the academic prestige of the institution to which it is affiliated.     

北京R&D投入与经济增长的灰色关联分析

随着科技投入的加大,R&D投入也越来越被人们所重视。R&D投入不仅对所在区域科技与经济发展具有重要作用,而且对整个国家的科技与经济发展都具有推动作用。本文运用北京2001~2011年R&D经费投入与经济增长的有关数据变量进行灰色关联分析,并根据不同结构建立了相应模型,揭示了北京R&D经费投入与经济增长的关系。     

Economic Impacts of Improved Connectivity for ASEAN: An Application of the Geographical Simulation Model

We compare the prioritized projects of the Master Plan on ASEAN Connectivity (MPAC) and the Comprehensive Asia Development Plan (CADP) by utilizing the Institute of Developing Economies/Economic Research Institute for ASEAN and East Asia Geographical Simulation Model. The prioritized projects of the MPAC mainly focus on specific hard or soft infrastructure projects connecting one remote area of an ASEAN member state to another and thus fail to capture the full potential of the infrastructure because of neglected important links within a state. On the other hand, the CADP emphasizes the importance of economic corridors or linkages between a large cluster and another cluster. Our simulation analysis shows that CADP projects will result in an addition to gross domestic product (GDP) of $US 1544bn over the period from 2021 to 2030 (in 2010 dollars) or an impact on ASEAN countries that is 12 times larger than MPAC projects. The results strongly suggest that the CADP projects should be adopted and implemented to fully realize the potential economic growth of the ASEAN countries. Moreover, the CADP will contribute more to narrowing the development gaps among the ASEAN countries than MPAC prioritized projects.     

Housing Allowance and the Rent of Low‐income Households

This paper analyses the effect of a housing allowance programme on the rent paid by assisted low‐income households. The data consist of 12,000 rental households in the free‐market and municipal sectors. The effect is estimated using the programme reform of 2002 as an instrument. The reform increased the allowance of the assisted households depending on housing characteristics, but it had little effect on the eligibility. Results suggest that in the private sector, one additional euro of allowance increases the rent of claimants by 60–70 cents. The effect is zero in the municipal sector, as rents are tied to the housing costs.     

Socioeconomic Determinants of Child Health: Empirical Evidence from Indonesia

This paper characterizes the socioeconomic determinants of child health using height‐for‐age z‐score (HAZ), a long‐run measure of chronic nutritional deficiency. We construct a panel data that follows children between ages 3 and 59 months in 1993 through the 1997 and 2000 waves of the Indonesian Family Life Survey. We use this data to identify the various child‐level, household‐level and community‐level factors that affect children's health. Our findings indicate that household income has a large and statistically significant role in explaining improvements in HAZ. We also find a strong positive association between parental height and HAZ. At the community level, we find that provision of electricity and the availability of paved roads are positively associated with improvements in HAZ. Finally, in comparison to community‐level factors, household‐level characteristics play a large role in explaining the variation in HAZ. These findings suggest that policies that address the demand‐side constraints have greater potential to improve children's health outcomes in the future.     

Capitalization of Flood Insurance and Risk Perceptions in Housing Prices: An Empirical Agent‐Based Model Approach

Federally regulated or insured lenders in the United States are mandated to require flood insurance on properties that are located in areas at high risk of flooding. Despite the existence of this mandatory flood insurance requirement, take‐up rates for flood insurance have been low, and the federal government's exposure to uninsured property losses from flooding remains substantial. Meanwhile, the value of capital at risk varies significantly with flood events and changing risk perceptions, which necessitates mechanisms that stabilize these dynamics. In this article we discuss how a scenario of complete insurance uptake, under various risk attitudes, affects the value of properties in the 100‐year and 500‐year flood zones. Our results indicate that an increase in flood insurance uptake may provide such a mechanism by lowering the value of capital at risk in the flood zone consistently, independent of homeowners' risk attitudes. We apply an empirical adaptive agent‐based model to examine the capitalization of insurance costs, risk premiums, and their interaction in housing prices. Our approach combines widely‐used empirical hedonic analysis with the computational economic framework. We highlight the usefulness of our method in capturing the marginal implicit price of homeowners' preferences that may change over time and separately assess the effect of various factors and policies on property values, illustrating the agent‐based modeling as a valuable complement to traditional hedonic analysis.     

Reasonable and Risk‐Based? Replacing NFIP Generally Subsidized Rates with a Means‐Tested Subsidy

The National Flood Insurance Program was created to seek two often conflicting goals: (i) shifting risks from federal taxpayers to those who choose to live in flood plains and (ii) ensuring flood insurance is available to everyone at “reasonable” rates. Efforts to accomplish the second goal currently take the form of subsidies based on location and the date a home was constructed. The resulting revenue from subsidized insurance premiums is not sufficient to cover the true cost of flood insurance, and federal taxpayers have paid the difference: $30 billion to date. Based on a detailed survey of households in the high‐risk flood zones of New York City (NYC), we find that replacing existing premium subsidies with risk‐based prices and a subsidy for low‐income housing‐burdened households could better meet both goals by ensuring low‐income individuals have access to affordable flood insurance while still saving the federal taxpayer up to $183 million per year in NYC alone.